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Fuzzy logic and fuzzy sets have been used successfully as tools to manage the uncertainty of fuzziness since their introduction in the 1960s, which have been applied to many fields, including [1–6]. The most widely used fuzzy systems are fuzzy rule-based inference systems, each comprising of a rule base and an inference engine. Different inference engines were invented to support different situations, such as the Mamdani inference engine [7] and the TSK inference engine [8]. The rule bases are usually extracted from expert knowledge or learned from data. The TSK model produces crisp outputs due to its polynomial rule consequences in TSK-style rule bases, while the Mamdani model is more appealing in handling inferences based on human natural language due to its fuzzy rule consequences. Despite of the wide applications, these conventional fuzzy inference mechanisms are only workable with dense rule bases which fully cover the entire input domain.
Fuzzy interpolation systems (FISs) were proposed to address the above issue [9], and they also help in complexity reduction for fuzzy models with too complex (dense) rule bases. If there is only a spare rule base available and a given input does not overlap with any rule antecedent, conventional fuzzy inference systems will not be applicable. However, FISs are still able to generate a conclusion by means of fuzzy interpolation in such situations, thus enhancing the applicability of conventional fuzzy inference systems. FISs can also improve the efficiency of complex fuzzy inference systems by excluding those rules that can be accurately interpolated or extrapolated using other rules in a complex rule base. Various fuzzy interpolation methods based on Mamdani-style rule bases have been proposed in the literature such as Refs. [9–20], with successful applications in the fields of decision-making support, prediction and control, amongst others.
FISs have also been developed to support TSK-style sparse fuzzy rule bases by extending the traditional TSK fuzzy inference system [21]. This approach was developed based on a modified similarity degree measure that enables the effective utilisation of all rules during inference process to generate a global result. In particular, the modified similarity measure guarantees that the similarity degree between any given input and any rule antecedent is greater than 0 even when they do not overlap at all. Therefore, all the rules in the rule base can be fired to certain degrees such that they all contribute to the final result to some extents and consequently a conclusion still can be generated even when no rule antecedent is overlapped with the given observation. The extended TSK fuzzy model enjoys the advantages of both TSK model and fuzzy interpolation, which is able to obtain crisp inference results from either sparse, dense or unevenly distributed (including dense parts and spare parts) TSK-style fuzzy rule bases.
FISs have been successfully applied to real-world problems. In some real world scenarios, neither complete expert knowledge nor complete data set is available or readily obtainable to generate evenly distributed dense rule bases. FISs therefore have been applied in such situations. For instance, a FIS has been applied to building evaluation in the work of Molnárka et al. [22] in an effort to help estate agencies making decisions for residential building maintenance, when some necessary relevant data have been lost. In Ref. [23], a FIS system was applied successfully to reduce the complexity and improve the efficiency of a fuzzy home heating control system. The work of Bai et al. [24] applied a FIS to calibrate parallel machine tools for industry use. A behaviour-based fuzzy control system is introduced in Ref. [25], which applied a FIS to make decisions when only incomplete knowledge base has been provided or available. Most recently, FISs have also been used to support network quality of service [26] and network intrusion detection [27].
The remainder of this chapter is organised as follows. Section 2 reviews the theoretical underpinnings of conventional fuzzy inference systems, that is, the Mamdani inference system and the TSK inference system. Section 3 discusses different fuzzy interpolation approaches to support sparse Mamdani-style rule bases. Section 4 presents the extension of the conventional TSK inference system in supporting sparse TSK-style rule bases. Section 5 reports two representative examples of fuzzy interpolation systems in the field of system control. Section 6 concludes the chapter and points out the directions for future work.
The process of fuzzy inference is basically an iteration of computer paradigm based on fuzzy set theory, fuzzy-if-then-rules and fuzzy reasoning. Each iteration takes an input which can be an observation or a previously inferred result, crisp or fuzzy. Then, these inputs are used to fire the rules in a given rule base, and the output is the aggregation of the inferred results from all the fired rules. There are generally two primary ways to construct a rule base for a given problem. The first way is directly translating expert knowledge to rules, and the fuzzy inference systems with such rule bases are usually called fuzzy expert systems or fuzzy controllers [28]. In this case, rules are fuzzy representations of expert knowledge, and the resultant rule base offers a high semantic level and a good generalisation capability. The difficulty of building rule bases for complex problems has resulted in the development of another approach of rule base construction, which is driven by data, that is, fuzzy rules are obtained from data by employing machine learning techniques rather than expert knowledge [29, 30]. In contrast, the rule bases built in this way lack comprehensibility and transparency. There are two types of rule bases depending on the expression of the consequences of the fuzzy rules composing the rule base. Mamdani-style fuzzy rules consider fuzzy terms or linguistic values in the consequence, while TSK-style fuzzy rules represent the consequences as polynomial functions of crisp inputs.
There are a number of fuzzy inference mechanisms that can be utilised to derive a consequence from a given observation using a Mamdani rule base. The two most significant modes are the compositional rule of inference (CRI) [31] and analogy-based reasoning [24, 33], which are introduced below.
The introduction of CRI marks the era of fuzzy inference [31]. Given a rule ‘IF x is A, THEN y is B”’ and an observation ‘x is A*’, the conclusion B* can be generated through CRI as:
where T is a triangular norm, sup represents supremum, and R is the relationship between variables x and y. Essentially, CRI is a fuzzy extension of classical modus ponens which can be viewed from two perspectives. Firstly, classical modus ponens only supports predicates concerning singleton elements, but CRI is able to deal with predicates which concern a set of elements in the variable domain. This is achieved by representing a fuzzy rule as a fuzzy relation over the Cartesian product of the domains of the antecedent and consequent variables. Various fuzzy implication relations have been proposed [7, 32–34], each of which may have its own properties and therefore is suitable for a certain group of applications. Secondly, classical modus ponens only supports Boolean logic, but CRI supports multi-value logic. That is, CRI is able to deal with predicates with partial truth values, which are implemented by a compositional operator sup T, where T represents a t-norm [35].
A number of existing fuzzy reasoning methods based on CRI have been developed [36, 37], including the first successful practical approach, that is, the Mamdani inference [28]. This approach is also the most commonly seen fuzzy methodology in physical control systems thus far. It was originally proposed as an attempt to control a steam engine and boiler combination by synthesising a set of linguistic control rules obtained from experienced human operators. Mamdani inference implements CRI using minimum as the t-norm operator due to its simplicity. In particular, the inferred result from each fired rule is a fuzzy set which is transformed from the rule consequence by restricting the membership of those elements whose memberships are greater than the firing strength. The firing strength is also sometimes termed the satisfaction degree, which is the supremum within the variable domain of the minimum of the rule antecedent and the given observation. A defuzzification process is needed when crisp outputs are required.
Despite the success of CRI in various fuzzy system applications, it suffers various criticisms including its complexity and vague underlying semantics [34, 38]. This has led to another group of fuzzy reasoning approaches which are based on similarity degree, usually called analogy-based fuzzy reasoning [38–41]. Similarity considerations play a major role in human cognitive processes [42], so do they in approximate reasoning. It is intuitive that if a given observation is similar to the antecedent of a rule, the conclusion from the observation should also be similar to the consequence of the rule. Different to CRI-based fuzzy reasoning, analogy-based fuzzy reasoning does not require the construction of a fuzzy relation. Instead, it is based on the degree of similarity (given a certain similarity metric) between the given observation and the antecedent of a rule. Utilising the computed similarity degree, the consequence of the fired rule can be modified to the consequence of the given observation.
Approximate analogical reasoning schema is a typical analogy-based fuzzy inference approach [34, 38]. In this method, rules are fired according to the similarity degrees between a given observation and the antecedents of rules. If the degree of similarity between the given observation and the antecedent of a rule is greater than a predefined threshold value, the rule will be fired and the consequence of the observation is deduced from the rule consequence by a given modification procedure. Another analogy-based fuzzy inference approach was proposed in Refs. [39, 40], which particularly targets medical diagnostic problems. This approach is based on the cosine angle between the two vectors that represent the actual and the user’s specified values of the antecedent variable. Several modification procedures can be found in Refs. [43, 44]. Particularly, a fuzzy reasoning method which employs similarity measures based on the degree of subsethood between the propositions in the antecedent and a given observation is proposed in Ref. [45]. This method has also been extended to consider the weights of the propositions in the antecedent [46]. Analogy-based fuzzy inference approaches usually arrive at solutions with more natural appeal than those introduced in the last section.
The TSK fuzzy inference system was proposed for the direct generation of crisp outputs [8]. In difference with the Mamdani-style fuzzy rule bases, TSK-style rule bases are usually generated from data using a clustering algorithm such as K-Means and an algorithm to determine the number of clusters such as Ref. [47]. Also, the consequence of a TSK fuzzy rule is a polynomial function rather than a fuzzy set. A typical TSK fuzzy rule can be defined as:
where A1,…Am are fuzzy values with regard to antecedent variables x1, …, xm respectively, and f(x1,…,xm) is a crisp polynomial function of crisp inputs determining the crisp output value. The rule consequent polynomial functions f(x1,…,xm) are usually zero order or first order. For simplicity, suppose that a TSK-style rule base is formed by two-antecedent rules as follows:
Suppose that (x0,y0) is the crisp input pair, then the inference process can be shown in Figure 1. As the input values overlap with both rule antecedents, both rules are fired. Using rules Ri and Rj, the given input then leads to system outputs fi(x0,x0) and fj(x0,x0), respectively. The consequences from both rules are then integrated using weighted average function, where the values of weights represent the matching degrees between the given input and the rule antecedents (often referred to as firing strengths). Assume that
TSK fuzzy inference [21].
where ∧ stands for a t-norm operator. Different implementations can be used for the t-norm operator, with the minimum operator being used most widely. Of course, if another system input (x1, y1) is presented and it is not covered by the rule base, the matching degrees between this new input and rule antecedents of Ri and Rj are equal to 0. In this case, no rule will be fired, and thus traditional TSK is not applicable. In this case, fuzzy interpolation is required, which is introduced in Section 4.
FISs based on Mamdani-style rule bases can be categorised into two classes. One group of approaches were developed based on the decomposition and resolution principle, termed as ‘resolution principle-base interpolation’. In particular, the approach represents each fuzzy set as a series of α-cuts (α ∈ (0,1]), and the α-cut of the conclusion is computed from the α-cuts of the observation and the α-cuts of rules. The final fuzzy set is assembled from all the α-cut consequences using the resolution principle [48–50]. The other group of fuzzy interpolation approaches were developed using the analogy reasoning system, thus termed as ‘analogy-based fuzzy interpolation’. This group of approaches firstly generates an intermediate rule whose antecedent maximally overlaps with the given observation, then the system output is produced from the observation using the intermediate rule. Two representative approaches of the two classes, the KH approach [10] and the scale and move transformation-based approach [9, 51, 52], are discussed in this section based on simple rule bases with two antecedent rules. Despite of the simple examples used herein, both of these approaches have been extended to work with multiple multi-antecedent rules.
Single step interpolation approaches are computationally efficient, such as the KH approach proposed in Refs. [9, 10, 53]. Following these approaches, all variables involved in the reasoning process must satisfy a partial ordering, denoted as ≺ [31]. According to the decomposition principle, a normal and convex fuzzy set A can be represented by a series of α-cut intervals, each denoted as Aα, α ∈ (0,1). Given fuzzy sets Ai and Aj which are associated with the same variable, the partial ordering Ai ≺ Aj is defined as:
where
Take the KH approach as an example here. For simplicity, suppose there are two fuzzy rules: If x is Ai, then y is Bi, and If x is Aj then y is Bj, shorten as Ai ⟹ Bi and Aj ⟹ Bj, respectively. Also, suppose that these two rules are adjacent, in other words, there is no rule A ⟹ B existing such that
where given any 0 < α ≤ 1, the distance
Following Eqs. (4) and (5), the following is resulted:
For simplicity, let
Also, denote
This means
The KH approach may generate invalid interpolated results [54], which is usually called ‘the abnormal problem’. To eliminate this deficiency, a number of modifications or improvements have been proposed, including Refs. [9, 10, 13, 14, 18, 53, 55–60]. Approaches such as Refs. [15, 16, 61–63] also belong to this group.
The scale and move transformation-based fuzzy interpolation [51, 52, 64] is a representative approach in the analogy-based interpolation group. For simplicity, following the same assumption of a simple rule base containing two rules with two antecedents, the transformation-based approach is shown in Figure 2 and outlined as follows.
Transformation-based fuzzy interpolation [12].
Given neighbouring rules If x is Ai, then y is Bi, and If x is Aj then y is Bj and observation A*, this method first maps fuzzy sets Ai, Aj and A* to real numbers ai, aj and a* (named as representative values) respectively, using real function f1. Then, the location relationship between A* and rule antecedents (Ai and Aj) is computed. This is achieved by another mapping function f2, which results in the relative placement factor λ. In contrast to the resolution-based interpolation approaches, the generated relative placement factor in analogy-based fuzzy interpolation approach is a crisp real number. Finally, linear interpolation is implemented using mapping function f3 of λ, which leads to the intermediate rule
Note that the representative value of intermediate rule antecedent
Fuzzy interpolation strengthens the power of fuzzy inference by enhancing the robustness of fuzzy systems and reducing the systems’ complexity. Common to both classes of fuzzy interpolation approaches discussed above is the fact that interpolation is carried out in a linear manner. This may conflict with the nature of some realistic problems and consequently this may lead to inconsistencies during rule interpolation processes. Adaptive fuzzy interpolation was proposed to address this [12, 66–68]. It was developed upon FIS approaches, which detects inconsistencies, locates possible fault candidates and modifies the candidates in order to remove all the inconsistencies.
Each pair of neighbouring rules is defined as a fuzzy reasoning component in adaptive fuzzy interpolation. Each fuzzy reasoning component takes a fuzzy value as input and produces another as output. The process of adaptive interpolation is summarised in Figure 3. Firstly, the interpolator carries out interpolation and passes the interpolated results to the truth maintenance system (ATMS) [69, 70], which records the dependencies between an interpolated value (including any contradiction) and its proceeding interpolation components. Then, the ATMS relays any β0-contradictions (i.e. inconsistency between two different values for a common variable at least to the degree of a given threshold β0 (0 ≤ β0 ≤ 1)) as well as their dependent fuzzy reasoning components to the general diagnostic engine (GDE) [71] which diagnoses the problem and generates all possible component candidates. After that, a modification process takes place to correct a certain candidate to restore consistency by modifying the original linear interpolation to become first-order piecewise linear.
Adaptive fuzzy interpolation [12].
The adaptive approach has been further generalised [11, 72, 73], which allows the identification and modification of observations and rules, in addition to that of interpolation procedures that were addressed in Ref. [12]. This is supported by introducing extra information of certainty degrees associated with such basic elements of FIS. The work also allows for all candidates for modification to be prioritised, based on the extent to which a candidate is likely to lead to all the detected contradictions, by extending the classic ATMS and GDE. This study has significantly improved the efficiency of the work in Ref. [12] by exploiting more information during both the diagnosis and modification processes. Another alternative implementation of the adaptive approach has also been reported in Ref. [74].
A Mamdani-style fuzzy rule base is usually implemented through either a data-driven approach [75] or a knowledge-driven approach [76]. The data-driven approach using artificial intelligence approach extracts rules from data sets, while the knowledge-driven approach generates rules by human expert. Due to the limited availability of expert knowledge, data-driven approaches have been increasingly widely applied. However, the application of such approaches usually requires a large amount of training data, and it often leads to dense rule bases to support conventional fuzzy inference systems, despite of the availability of rule simplification approaches such as Refs. [77, 78].
A recent development or rule base generation has been reported with compact sparse rule bases targeted [79]. This approach firstly partitions the problem domain into a number of sub-regions and each sub-region is expressed as a fuzzy rule. Then, the importance of each sub-region is analysed using curvature value by artificially treating the problem space as a geography object (and high-dimensional problem space is represented as a collection of sub-three-dimensional spaces). Briefly, the profile curvature of a surface expresses the extent to which the geometric object deviates from being ‘flat’ or ‘straight’, the curvature values of the sub-regions are then calculated to represent how important they are in terms of linear interpolation. Given a predefined threshold, important sub-regions can be identified, and their corresponding rules are selected to generate a raw sparse rule base. The generated raw rule base can then be optimised by fine-tuning the membership functions using an optimisation algorithm. Generic algorithm has been widely used for various optimisation problems, such as Ref. [80], which has also been used in the work of Ref. [79].
Compared to most of the existing rule base generation approaches, the above approach differs in its utilisation of the curvature value in rule selection. Mathematically, curvature is the second derivate of a surface or the slope of slope. The profile curvature [81] is traditionally used in geography to represent the rate at which a surface slope changes whilst moving in the direction, which represents the steepest downward gradient for the given direction. Given a sub-region f(x, y) and a certain direction, the curvature value is calculated as the directional derivative which refers to the rate at which any given scalar field is changing. The overall linearity of a sub-region can thus be accurately represented as the maximum profile curvature value on all directions. From this, those rules corresponding to sub-regions with higher profile curvature values (with respect to a given threshold) are selected, which jointly form the sparse rule base to support fuzzy rule interpolation.
FISs relax the requirement of complete expert knowledge or large data sets covering the entire input domain from the conventional fuzzy inference systems. However, it is still difficult for some real-world applications to obtain sufficient data or expert knowledge for rule base generation to support FISs. In addition, the generated rule resulted from most of the existing rule base generation approaches are fixed and cannot support changing situations. An experience-based rule base generation and adaptation approach for FISs has therefore been proposed for control problems [82]. Briefly, the approach initialises the rule base with very limited rules first. Then, the initialised rule base is revised by adding accurate interpolated rules and removing out-of-date rules guided by the performance index from a feedback mechanism and the performance experiences of rules.
The traditional TSK inference system has been extended to work with sparse TSK fuzzy rule base [21]. This approach, in the same time, also enjoys the benefit from its original version, which directly generates crisp outputs. The extended TSK inference approach is built upon a modified similarity measure which always generates greater than zero similarity degrees between observations and rule antecedents even when they do not overlap at all. Thanks to this property, a global consequence can always be generated by integrating the results from all rules in the rule base.
The modified similarity measure is developed from the work described in Ref. [83]. Suppose there are two fuzzy sets A and A′ in a normalised variable domain. Without loss generality, a fuzzy set with any membership can be approximated by a polygonal fuzzy membership function with n odd points. Therefore, A and A′ can be represented as
An arbitrary fuzzy set with n odd points.
where cA is the centre of gravity of fuzzy sets A, and μ(cA) is the membership of the centre of gravity of fuzzy set A; DF represents a distance factor which is a function of the distance between two concerned fuzzy sets, and
where suppA and suppA′ are the supports of A and A′, respectively.
In Eq. (13),
The distance factor DF is represented as:
where d is the distance between the two fuzzy sets, and h(h > 0) is a sensitivity factor. The smaller the value of h is, the more sensitive the similarity degree to their distance is. The value of h is usually within the range of (20, 60), but the exact value is problem specific.
Using the modified similarity measure as traduced above, the similarity between any given observation and a rule antecedent is always greater than zero. This means that all the rules in the rule base are fired for inference. Therefore, if only a sparse rule base is available and a given observation is not covered by the sparse rule base, a consequence still can be generated by firing all the rules in the rule base. The inference process is summarised as below:
Calculate the matching degree
Determine the firing strength of each rule by integrating the matching degrees between the input items and rule antecedents as calculated in Step 1:
Compute the consequence of each rule in line with the given input and the polynomial function in rule consequent:
Obtain the final result z by integrating the sub-consequences from all m rules in the rule base:
Fuzzy interpolation systems have been successfully applied to a number of real-world problems including Refs. [23, 22, 25, 52, 57], two of which are reviewed in the section below.
Backing a trailer truck to a loading dock is a challenging task for all yet the most skilled truck drivers. Due to the difficulties, this challenge has been used as a control benchmark problem with various solutions proposed [75, 84, 85]. For instance, an artificial neural network has been applied to this problem, but a large amount of training data is required [84]. An adaptive fuzzy control system was also proposed for this problem, but the generation of the rule base is computationally expensive. Another solution combines empirical knowledge and data [85]. That is, a combined fuzzy rule base is generated by joining the previously generated rules (data-driven) and linguistic rules (expert knowledge-driven). More recently, a supervisory control system was proposed with fewer number of state variables required due to its capability to the decomposition of the control task, thus relieving the curse of dimensionality [86].
Fuzzy interpolation system has also been applied to the trailer truck backer-upper problem [52] to further reduce the system complexity. The problem can be formally formulated as
If the traditional fuzzy inference system were applied, the sparse rule base would cause a sudden break of the truck for some situations as no rule would be fired when the truck is in the position that can be represented by the omitted rules. In this case, fuzzy interpolation is naturally applied and the sudden break problem can be avoided. In addition, thanks to the great generalisation ability of the fuzzy interpolation systems, smooth performance is also demonstrated compared to the conventional fuzzy inference approaches. This study clearly demonstrates that fuzzy interpolation systems are able to simplify rule bases and support inferences with sparse rule bases.
The demotic energy waste contributes a large part of CO2 emissions in the UK, and about 60% of the household energy has been used for space heating. Various heating controllers have been developed to reduce the waste of energy on heating unoccupied properties, which are usually programmable and developed using a number of sensors. These systems are able to successfully switch off heating systems when a property is unoccupied [88–92], but they cannot intelligently preheat the properties by warming the property before users return home without manual inputs or leaving the heating systems on unnecessarily for longer time. A smart home heating controller has been developed using a FIS, which allows efficient home heating by accurately predicting the users’ home time using users’ historic and current location data obtained from portable devices [23].
The overall flow chart of the smart home heating system is shown in Figure 5. The controller first extracts the resident’s location and moving information. There are four types of residents’ location and moving information that need to be considered: At Home, Way Back Home, Leaving Home and Static (i.e. at Special Location). The user’s current location and moving states are obtained effectively using the GPS information provided by user’s portable devices. From this, if the resident’s current state is At Home, the algorithm terminates; and if the residents’ current state is Leaving Home, that is the residents are moving away from home, the boiler is off and the system will check the resident’s location and moving information again in a certain period of time. Otherwise, the time to arriving home (denoted as TAH) is predicted and the time to preheat the home to a comfortable temperature (denoted as TPH) is also calculated, based on the resident’s current situation and the current environment around home.
The flow chart of the heating controller [23].
The user’s current travel modes (i.e. driving, walking or bicycling) can be detected by employing a naïve Bayes classifier [93] using the GPS information. Then the travel distance and time between the current location and home can be estimated using Google Distance Matrix API. Note that the time spent on different locations may vary significantly, and also different residents usually spend different amount of times at the same special location as people have their own living styles. The time that the residents spent at the current location is therefore estimated using fuzzy interpolation systems, thanks to the complexity of the problem. In particular, the fuzzy interpolation engine takes five fuzzy inputs and produces one fuzzy output which is the estimate of the time to getting home. The five inputs are the current location, the day of the week, the time of the day, the time already spent at the current location and the estimated travel between the current location and home.
If each input domain is fuzzy partitioned by 5 to 13 fuzzy, tens of thousands of rules will be resulted which requires significant resources during inferences. The proposed system, however, has selected the most important 72 rules forming a sparse rule base to support fuzzy rule interpolation, which significantly improve the system performance. Once the home time is calculated, the home can then be accurately preheated based on a heating gain table developed based on the particular situation and environment of a concerned property [91]. This work has been applied to a four-bedroom detached house with a total hearing space of
Despite of the success of the applications introduced above, there is a potential for FISs to be applied to more and larger scales real-world problems, especially in the field of system control. Note that robotics has taken the centre in the control field to perform tasks from basic robot calligraphy system [94] to complex tasks which require hand-eye (camera) coordination [95]. FISs can also be applied to such advanced areas in the field of robotics, which require further investigation.
This chapter reviewed fuzzy interpolation systems and their applications in the field of control. There are basically two groups of fuzzy interpolation approaches using the two most common types of fuzzy rule bases (i.e. Mamdani-style rule bases and TSK-style rule bases) to supplement the two groups of widely used fuzzy inference approaches (i.e. the Mamdani inference and the TSK inference). The applications of fuzzy interpolation systems have also been discussed in the chapter which demonstrate the power of the approaches. FISs can be further improved despite of its promising performance. Firstly, type-2 FISs have already been proposed in the literature, but how type-2 FISs can be applied in real-world applications requires further investigation. Also, more theoretical analysis for FISs is needed to mathematically prove the convergence property of the approaches. In addition, most of the existing fuzzy interpolation approaches are proposed as a supplementary of the existing fuzzy inference models. It is interesting to investigate the development of a united platform which integrates both the existing fuzzy models and fuzzy inference systems such that the new system can benefit from both approaches.
This work was jointly supported by the National Natural Science Foundation of China (No. 61502068) and the China Postdoctoral Science Foundation (Nos. 2013M541213 and 2015T80239).
We live in a business civilization. What businesses do and how they operate extensively affect all areas of contemporary life both in industrialized societies and worldwide. Several contemporary trends are deeply disturbing – regarding climate change and other environmental concerns, the reduction in employment opportunities, and increasing inequality with regard to wealth. To a significant degree each of these problems grows out of the ways businesses have been operating. These problems have become more aggravated since the 1970s in spite of the noteworthy efforts by many businesses to address these concerns during this same period of time. Many businesses have committed themselves to foster social responsibility, environmentally sustainable practices, ethically informed conduct, and more responsible governance. These efforts have made a significant difference but the trends to which I have referred remain disturbing. Accordingly, while supporting these diverse efforts to foster socially and environmentally responsible business practices, it is time as well to undertake some fundamental re-thinking about underlying character and purposes of business enterprises. What is and what should be the business of businesses? Typically how are critical decisions made and how should they be made? These are vital questions because the disturbing trends with respect to the environment, the reduction of employment opportunities, and increased inequality in wealth seem to be closely connected with the current financial model regarding the character and purposes of business activity.
\nI will begin this project in “re-thinking” by analyzing these trends and the ways current businesses practices contribute to them. To begin with, we see around us evidence of considerable environmental damage directly and indirectly caused by how businesses operate. These include climate change, the pollution of both fresh and ocean waters, deforestation and soil degradation in many areas, and depletion at anxiety-provoking rates of a number of non-renewable minerals. Climate change has already occasioned increases in more destructive storms, droughts, forest fires, lands lost to rising sea levels, and the migrations of millions of people forced to leave where they had been living because of these conditions. Despite the commitment of many businesses to sustainability, these disturbing trends have continued. In the second place, many people worry as well about the ways current business practices have become associated with the disappearance of jobs, both because more goods and services are being produced by workers in other countries and because more and more tasks that used to be performed by laborers are now being performed, or will in the not too distant future be performed, by smart machines. In spite of contemporary lower rates of formal unemployment in some industrialized countries, rates of underemployment have markedly grown as have the rates of working age men and women who have simply dropped out of the labor force. A goodly portion of the reduction in full time employment has occurred not just as the results of technological changes and globalization but because of increasing use of temporary workers and the steady decrease in the share of business earnings devoted to paying for labor and the increasing portion devoted to paying investors. The rates of joblessness are likely to increase steadily in the future unless we act in some ways to address this issue. The consequence of these trends for family life, political processes, and community activities has been and are likely to continue to be very disturbing. Finally, although rates of extreme poverty have declined globally as have the rates of income inequality between countries, the rates in inequality in wealth have increased steadily over the past four decades. These rates of inequality have increased in part because low and middle income households have not appreciably gained in their wealth but even more because the wealthy have found more ways to enhance and protect their wealth. Businesses generally and businesses in the financial sector especially have contributed to these trends by creating more ways of accumulating and protecting financial wealth.
\nThese trends have become more aggravated since 1970s. Since that time a number of taken for granted assumptions about what businesses are in the business for have also changed in small but profound ways. Increasingly the normative assumption that chief purpose of businesses is to provide a healthy return to their investors has been regarded like an obvious descriptive account of the basic nature of businesses. As Milton Friedman wrote in 1970, albeit still using normative terms, “The primary social responsibility of business is to make a profit.” It has become a widely accepted assumption that most businesses, if not otherwise restrained or inspired, will make their critical decisions with the aim of maximizing their financial worth as gauged by their potential value if sold or the current value of their shares on financial markets. These assumptions about nature and purposes of businesses is well-illustrated by the current response of businesses to the announcement of Blackrock Investors that it would remove investments from firms that failed to operate in keeping with sustainability guidelines. Accordingly, because what really counts are financial returns, businesses will even adopt sustainable business practices if they can thereby attract and keep investors. I will elaborate on this analysis further along in this essay. Here, I simply want to call attention to the way the financial model of the nature and purposes of business has become more ascendant since the 1970s. Furthermore, this model, which is of course normative, is widely regarded as describing the taken for granted reality of how businesses by nature operate. This financial model is widely invoked to describe the basic nature of businesses in much the same manner as gravity is invoked to describe why planets circle around the sun or why prices go up when supply drops and demand increases.
\nThe financial model for how business enterprises operate has gained widespread support for a number of reasons. It has, for example, been assumed that as businesses function in keeping with this model the economies as a whole have tended to grow, standards of living have improved, and customers have benefit. These are, of course, discussable if not debatable conclusions. It has been further assumed that, if sometimes when enterprises do businesses in compliance with this model they occasion adverse consequences, then companies can minimize or compensate for these adverse side effects by engaging in corporate social responsibility and sustainability practices. Fundamentally, it has been widely assumed that the financial model for business enterprises provides the most fitting way of describing the basic feature of the core business of businesses while also providing a workable framework for measuring how well businesses are in fact doing. Business enterprises have often become quite complex realities at once engaging with multiple stakeholders. In the past over many years, business people often attempted to gain a good sense of how well their enterprises were doing by variously reviewing their relationships with employees, customers, suppliers, creditors, and/or competitors. Often, to be sure, these surveys resulted in imprecise and incomparable assessments. Accordingly, it has seemed convenient to many business people to gauge the overall wellbeing of their enterprises by consulting a single measure, such as their financial value. Over time, the financial model has gained wider acceptance at the same time as investors have gained greater control over business enterprises [1, 2].
\nIt has been possible to mount a very compelling case for the credibility and reliability of this model based on the assumption that any increases in value of financial investments were residual in principle and, it was assumed, in practice. According to this assumption, business enterprises are in principle expected to use their earnings first to pay their employees, their suppliers, their rents, their debts, and their taxes, to make appropriate upgrades in their operation, and then to use what remains to benefit their investors. Correspondingly, if businesses enterprises are doing so well that they can meet their regular expenses and still reward their investors, then to that degree, it has been assumed, enterprises must be doing very well indeed [3]. In practice, however, payments to investors are often assigned priority as evidenced by the disturbing trends I just described as well as the steady decrease in the proportion of business earnings being used to pay for labor costs and increases in the proportion used to pay investors.
\nIt is possible to identify in a number of different ways how the ascendancy of the financial model for business enterprises has fostered adverse outcomes environmentally and socially. For example, many businesses have refused voluntarily to reduce both toxic emissions and pollution unless legally required. As they often explained, they could not afford these extra expenses without significantly reducing their financial returns or raising prices for their products. In the early 1980s many traditional manufacturing firms failed to invest funds in upgrading their productive technology because of high short term costs of these investments, even though lack of these upgrades eventually rendered them less competitive to foreign competitors. Although in Nigeria it did invest in exemplary ways in a number of CSR type programs over the years, nevertheless, in ways that would later occasion much trouble for itself, Shell Nigeria initially failed to bury its pipelines and failed to explore ways of using excess gas to generate and distribute electricity. Instead it flared 85% of this gas, thus both occasioning pollution and wasting a very valuable resource. Given the expectation of their investors during the 60s, 70s, 80s, and 90s, Shell Nigeria simply did not consider these alternatives [4].
\nIn addition, since the 1970s, businesses generally have found they can reduce their expenses and make higher returns for investors by investing in technologies that reduce the need for workers. Smart machines have been installed to make automobiles and many other manufactured products. In ever greater numbers smart machines are undertaking clerical work. In addition, in order to reduce labor costs, firms both contract with external suppliers for a number of their services and supplies rather than undertaking these operations themselves and they hire increasing portions of employees on a part time and temporary basis, thereby often freeing themselves from having to pay fringe benefits [5]. As a result of these strategies, post-tax corporate profits in the United States increased from an average of 5% GDP in 2000 to between 8% and 9% for the 2010s. If profit levels had remained at 5% of GDP, than average wage levels would be 6% higher [6]. With a measure of alarm a number of recent observers have called attention to the dramatic decline in employment opportunities over the past several decades [7, 8, 9]. Official rates of unemployment hide the problem, because increasing number of adults have either dropped out of the labor market or are working in temporary jobs part time or part year. After surveying both current trends and informed estimates of future developments, Yang describes the sizeable decline in employment opportunities that has happened and will happen in factory work, trucking, clerical positions, legal firms, and even therapy [10]. Of course, the current pandemic has rendered the situation of employees even more precarious.
\nIn addition to factors I have already discussed, the financial model has in practiced operated to increase the wealth of the wealthy in several other ways. For example, many businesses have deliberately incorporated or established their headquarters in jurisdictions with very low or no corporate taxes. Many businesses have also established subsidiaries in these tax havens again to reduce their taxes and increase thereby their overall financial value [11, 12]. Interestingly, much of the effort put into fostering responsible governance of business has been designed at reducing the arbitrary activities of senior executives and at increasing the influence of Boards of Directors, who are in turn in many countries primarily expected to represent the interests of investors. Furthermore, along the same lines, while the compensation levels of executives have greatly increased, much of that increase has assumed the form of paying executives with larger portfolios of shares in their own companies, thereby instilling and reinforcing an intrinsic interest for executives in augmenting the financial value of their firms. In practice the ascendancy of the financial model has been closely associated as well with the growth of large firms within particular markets. As the financial value of particular firms grow, they become able to buy out competitors, thereby increasing the concentration and near monopoly power of these financially successful enterprises. This has become a seriously worrying trend. In 1980 the aggregate revenues of the 1000 largest firms represented 30% of the GDP of the OECD countries. By 2010 the aggregate demand of the 1000 largest firms had increased to represent 70% of the GDP of these countries [13]. Thomas Piketty has argued that the wealth of the wealthy increases naturally as a characteristic feature of industrialized market economies [14]. In contrast, I think that recent increases in the wealth of the wealthy results from discrete policy decisions not only by national governments but also by the way many business enterprises are organized and governed.
\nWe can find much evidence to demonstrate that operating business operations in keeping with the financial model has aggravated environmental problems, reduced employment opportunities, and increased inequalities in wealth. These all represent disturbing trends. To be sure, in keeping with this model, many businesses have increased their financial value and as a whole financial markets have greatly expanded. From the perspective of the financial model, the overall economies of most countries seem comparatively healthy with a few incidental problems. And the latter might well be addressed, so the defenders of this model contend, by more vigorous business social responsibility initiatives. However, if we think these environmental and social consequences as well as disparities in wealth represent very serious problems, then we are indeed called upon to see if there are other models for operating businesses that might be both viable and less likely to occasion such adverse consequences.
\nAs a way of understanding and managing businesses, the financial model – often referred to as the shareholder model – has been criticized by a number of observers and interested parties. A number of pension funds have lobbied business to adopt more sustainable practices. Most recently the Business Roundtable, an influential association of chief executives in the United States, made a strong case for adopting the stakeholder model of the firm and thinking about the purposes of business in relation to this model. Acknowledging the vital role that businesses play “creating jobs, fostering innovation, and providing goods and services,” the statement signed by more than 200 chief executives, on behalf of their companies, asserted their “fundamental commitment to all our stakeholders.” [15] The Business Roundtable expressed an important but modest commitment to an understanding of productive enterprises, now viewed in relation to multiple stakeholders. This statement expressed no overt commitment towards alternative views of corporate governance that might, like policies adopted in Germany, for example, provide for greater representation of workers on corporate boards. Even so, the Economist magazine initially was so alarmed by this statement that it argued in a lead editorial that “this new form of collective capitalism will end up doing more harm than good.” Overlooking the way the German model of governance has operated in practice to render executives more responsive and responsible to several stakeholders on whose contributions their businesses depend, the Economist editorial instead opined that the model proposed by the Business Roundtable “risks entrenching a class of unaccountable CEOs who lack legitimacy.” [6] One might argue that the stakeholder model favored by the Business Roundtable actually increases while broadening the accountability of chief executives. In any case, the Business Roundtable maintains, as I maintain in this essay, that the business of business is to foster productivity, rightly understood, in ways that enhance the wellbeing of the enterprises as a whole and fittingly benefits all of their stakeholders.
\nAccordingly, in addition to promoting various socially and environmentally responsible business practices, if we are concerned about the trends discussed above, then we must also consider if there are acceptable alternatives to the currently almost universally taken for granted financial model for conceiving of the business of business. We must acknowledge that some proposed alternatives, such as state ownership of enterprises, would not in many countries be acceptable either politically or economically. Acceptable alternatives must in some ways be in accord with widely shared values, traditional practices, and existing realities. And they must be practical.
\nIn the remainder of this essay I will make the following argument. Business enterprises ought to operate in keeping with the stakeholder model as proposed by the Business Roundtable both because operating in keeping with this model will go a long ways in reducing the adverse impacts described above and because this model more accurately describes what businesses actually do and how businesses produce what they produce. Accordingly, the social responsibility of businesses can best be represented not as the mandate to make profits but as the mandate of enterprises to make productive use of natural and human resources in order in diverse and fitting ways to add value to their stakeholders and thereby to the larger society and to use the resources of the Earth respectfully and sustainably. Furthermore, enterprises can and should measure how their interactions with their several stakeholders add and erode economic value in diverse ways. They can undertake these assessments using increasingly more sophisticated measures developed over the past several decades. In order to realize the advantages of the stakeholder model and thereby protect and increase productivity, righty understood, governance practices of many enterprises must be adjusted and reformed so that governing boards have a vested interest in enhancing the well-being of the enterprise as a whole rather than the wellbeing of particular, privileged stakeholders, such as investors. Finally, in order to realize these several objectives, it will be necessary in many countries to introduce some corresponding legal changes facilitating and supporting these objectives. For the most part, it is possible to find examples of these kinds of legal changes that have already been introduced in a number of countries. The aim overall is to maintain and enhance the productivity of business enterprises, rightly understood, in ways that benefit these enterprises as a whole and thereby the larger societies in which they operate and the Earth whose resources they count on and utilize.
\nTo begin, then, we know that the financial model represents only one of several alternatives ways of understanding the business of businesses. For example, producer cooperatives have been organized to maximize the benefits for workers and retail cooperatives have been established to maximize the benefits for consumers. These are genuine alternative models although probably relevant only to a small number of firms. So long as they were able to meet their expenses, many businesses traditionally have seen their purposes largely as providing particular goods and services they have taken pride in providing and in providing good employment for their workers. For many years many businesses were organized in this manner [1, 2]. Certainly, many professional businesses – whether they have been offering medical care, architectural services, legal assistance, or educational opportunities – continue to see themselves in these lights. So, there are viable bases for considering alternative ways of understanding the purposes of business.
\nIt is time to re-consider the viability of the financial model of business enterprises not only because there seems to be a correlation between acting in keeping with this model and the rise in disturbing environmental, social, and economic consequences, but also because this model provides a distorted account of how businesses in fact operate. This model provides an imbalanced view of what businesses do, over emphasizing the financial agenda and focusing less attention on the many other goals that business enterprises seek to realize.
\nBusinesses are complex organizations best described not as things but as sets of overlapping and interacting activities. Oliver Williamson once argued that business enterprises are most fittingly characterized as the nexus of treaties or contractual relationships [16]. While this characterization is indeed helpful, it is not quite accurate because the relationships of businesses with some of their more vital constituents, such as retail customers and some affected community groups, are frequently not strictly contractual. In addition, Williamson’s model does not focus enough on the activities by which businesses engage in business. Utilizing the sociological perspective associated with Symbolic Interaction, we can I think more fittingly observe that business enterprises are the nexus of usually negotiated, often legally recognized, value-adding interactions with diverse constituencies (1). Depending on the particular enterprise, the number and the importance of these diverse stakeholders vary. Nonetheless, each of these interactive relationships -- whether they be with employees, supplier, creditors, investors, competitors, or other constituencies – function both to create and to reduce value for the enterprise as a whole, contingent upon the benefits and costs associated with these relationships. To be sure, those managing enterprises work at managing effectively so that each of these sets of interactions become more value-adding than value-decreasing. At the same time, each of these interactive relationships exposes particular constituents to different kinds of characteristic risks. Moreover, based on expectations variously spelled out in negotiated contracts, laws, and/or changing societal mores, each of these constituencies are in position to make particular kinds of claims on business enterprises in relation to the character of their interactions (2).
\nViewed from this perspective, it is not quite correct to argue that business enterprises have stakeholders. Using this kind of language makes it seem as if these constituencies were external to business enterprises. Rather, it is more accurate to acknowledge that business enterprises are constituted in the first place by establishing interactive relationships with several different stakeholders. Without these interactive relationships, they would not be in business.
\nWhile it is useful to think of business enterprises as nexus of value-creating interactions, and correspondingly to recognize that the boundaries of businesses are often porous and flexible [17], it is important to add that business enterprises are entities. They are indeed complex, interactive entities. They are also inherently productive entities. By utilizing natural and human resources, business enterprises produce goods and services to meet the needs and wants of consumers. As entities, correspondingly, the core responsibility of businesses is to promote the wellbeing of their overall operations and not only and not even primarily the well-being of particular stakeholders, whether these be their investors or employees. The good of business is to promote the good of this complex, interactive entity as a whole. Beginning two centuries ago, courts in the United States affirmed this view by regarding business enterprises as if they were – not real but – legal persons: that is, as distinct kinds of legally-recognized social beings. The current interest in assessing businesses in relation to integrated standards, like the Global Reporting Initiative, take account of the overall ways businesses add and erode value and also reflect this insistence on regarding business as a whole.
\nWhat has been especially characteristic of business enterprises is their productivity. They are and they become “productive” to the degree that they utilize given natural and human resources to add economic value to societies. They do so in multiple ways. For example, whether they be farms producing food, manufacturers producing mobile phones, or real estate firms helping people to buy and sell houses, business enterprises add value to society through the goods and services they produce. To the extent that they meet the needs and wants of people, these goods and service are paid for and valued. At the same, business enterprises add economic value to society both through the wages and salaries paid workers employed to produce these goods and services and through earnings paid to suppliers who supply the resources and tools businesses use to provide these products. Furthermore, business enterprises add economic value to society through the taxes they pay, the profits they generate, the returns they make to creditors, and rents they may pay. The productivity of businesses grows out of the multiple interactive relationships by which each business enterprise engages in its particular business.
\nIn this essay I am primarily gauging the productivity of enterprises in relation to the economic values they generate rather than in relation to social values. The latter are significant and must be taken into account, in relation both to values added and values eroded. After all, as a whole businesses enterprises have operated to create many of the goods and services that have functioned to enhance life conditions in modern societies. In addition, businesses provide workers not only sources of income but also jobs. The latter have often been associated with a wide range of social benefits including opportunities to experience agency, routines, valued social relations, and play-like opportunities to compete in addition to social costs, which have often been noticed, like experiences of drudgery and oppressive supervisors. Businesses have often fostered feelings of community among workers and with the locales in which they are located. In addition, in ways most famously noticed by the sociologist Emile Durkheim, modern business enterprises as the nexus value-creating interactions help to bring into being a larger sense of social inter-relatedness Durkheim referred to as organic solidarity [18]. However, while I think it is indeed very important overtly to acknowledge these and other social values of business enterprises, I am primarily analyzing in this essay the ways economic value of firms have been too narrowly understood by the financial model. This model not only fails to appreciate the wide range of ways business enterprises add economic value to society but it fails appropriately to acknowledge the economic costs it imposes on many of its stakeholders, the larger society, and the Earth [19, 20].
\nOver time, business enterprises have become more productive. They have increased the several different economic values they generate as a result of a number of noteworthy developments. These include finding and utilizing more effective sources of energy, developing cleverer and more effective tools, organizing business operations in ways that better facilitate working arrangements [21] and utilizing more effective means for storing and communicating information. In all of its different forms, productivity takes place and increases as business enterprises find ways of utilizing natural and human resources more effectively. Correspondingly, productivity is best measured by calculating the overall value that their productive process add to the basic natural and human resources they utilize, taking into account at the same time the costs incurred in accessing and utilizing these resources.
\nThese costs assume many different forms. For example, if a business enterprise needs funds, it must be ready to pay interest on loans and/or profits to investors. They must also operate in ways so that investors remain confident that they will earn a fair return on their investments. There are, to be sure, costs involved in how businesses operate in order to gain and maintaining that confidence. In order to acquire the supplies they need, businesses have to develop reliable relationships with all sorts of suppliers, always seeking to find the best quality and most reliable supplies accessed at the most reasonable prices. All these are comparatively straight-forward, widely understood costs. Costs become less clearly defined and a bit more complex with respect to the utilization of natural resources. Costs here include not only the price to access these resources (that is, to extract and transport them) but also the often hidden costs incurred in so far as the process of accessing these resources in turn reduces the overall supply of these resources and/or degrades the environment from which businesses take these resources. Accordingly, in so far as the processes of accessing natural resources – whether these be agricultural and forestry goods, minerals, air, water, and energy sources – are not strictly environmentally sustainable, then these processes give rise to added costs. These added costs have typically not been borne by enterprises themselves but by the society at large, later generations, and the Earth itself. Many observers today argue that businesses must also take into account the less tangible benefits they enjoy from ecosystem services provided by the Earth, its climate, and its biosphere [22].
\nThe overall costs incurred for obtaining an adequate and appropriately skilled supply of labor are also not so neatly defined. On the surface, it seems relatively simple. Enterprises seek workers through labor markets to work under certain terms and pay them at rates comparable to similar enterprises. In keeping with these terms, workers may work part time or full time; they may be paid by their output or time worked; and they may be paid a salary, wage and/or shares or bonuses. Many enterprises incur additional costs associated with recruiting and later training potential employees. However, from the perspective of the larger society, there are a number of other costs associated with labor markets. For example, societies incur the costs of educating potential workers, helping to develop basic skills of numeracy and literacy, skills at problem solving and communicating, as well as specialized skills associated with specific trades and professions. Societies face additional costs of providing unemployment insurance, pensions, and workmen’s compensation to that extent needed when potential workers are unable to work.
\nSocieties face a number of additional cost that emerge as they seek to develop physical, social, legal, and economic infrastructures that help to create the conditions so that businesses can engage in business. They must develop appropriate physical infrastructures – roads, rail lines, supplies of water, sewage systems, garbage collection, telephone lines, and supplies of electricity –without which businesses cannot do business. Businesses also require social infrastructures – systems for health care, policing, social welfare, and education, to which I have already referred. Business also counts on societies providing legal infrastructures, to protect their contracts and property, allow for negotiated exchanges, and the judicial review of conflicts. Businesses greatly benefit to the extent that particular societies are able to develop these legal infrastructures [23]. Although the systems vary, most business enterprises pay taxes in exchange for benefits they receive from the societies in which they operate. It is a matter of ongoing debate, whether the taxes businesses pay adequately reimburse governments for all the cost entailed in developing and maintaining these physical, social, and legal infrastructures.
\nIf we are to measure the productivity of business enterprises adequately and accurately, then we are challenged to find ways of measuring the overall value these enterprises add to societies less the several different costs they occasion. Before we address the question of how businesses might in practical ways calculate these added values and attendant costs, it is useful to observe that this understanding of productivity differs significantly from that the typical taken-for-granted ways of understanding productivity. Typically, productivity is thought of as increases in the economic output in relation the amount of labor involved. Accordingly, if an enterprise can produce the same amount of goods and services using either fewer workers or the same number of employees working fewer hours, then these changes are regarded as representing increases in productivity. These changes might be brought about by re-organizing patterns of work, improving the skill level of workers, and/or making greater use of technology. This view of productivity directly reflects assumptions built into the financial model of business enterprises. Thus, everything else being equal, enterprises are regarded as being more productive if their production of goods and services yields more value to owners and investors as labor costs are reduced.
\nAlthough this understanding of productivity is widely accepted, it is flawed in a number of ways. In the first place, productivity ought to be measured not just financially in relation to added value for investors but also in relation to earnings of laborers as well as benefits to other relevant stakeholders including suppliers and the larger society. As I have already noted, societies benefit from the productivity of businesses in many ways. In the second place, productivity should also take into account the various overt and hidden costs incurred by all stakeholders who contribute to the productive process. Much attention has been directed, for example, at the ways business enterprises have failed to pay the true costs of their uses and abuses of natural resources. In so far as business operations reduce or exhaust mineral and hydrocarbon resources, degrade soils, pollute the atmosphere or water systems, these are real costs that must be taken into account. If we accurately take account of these costs, we would realize that standard measures of productivity often in distorted ways overlook these costs. I think a case can also be made that while the standard way of gauging productivity with respect to the utilization of labor may often adequately represents the situation of individual enterprises, it misrepresents what is happening in labor markets for societies as a whole. It can be argued that well-functioning labor markets ought to help both enterprises find the workers they need and for workers to find the remunerative positions they seek. Sub-employment occurs when working age adults who would prefer to work find themselves unemployed, under-employed, or dropped out of the labor market. Because the costs for sub-employment are borne by these individuals, their households, and the larger society, individual enterprises do not typically take these costs into account when gauging their own productivity. Nonetheless, these represent real costs that must be considered when gauging the overall productivity of business activity.
\nBusinesses enterprises are complex, productive organizations, whose productivity should be – and can be – measured in relation to the several ways they add economic value and occasion economic costs. Clearly, assessing the degree to which businesses add economic value to society by taking into account the value added with regard to the utilization of labor, societal resources, as well as natural resources, is a more complex, multi-dimensional exercise than assessing the value added strictly in financial terms. In order to realize this fuller objective, a number of initiatives have been undertaken to develop practical means for calculating these values and costs not only in relation to financial assets but also natural resources, labor assets, and social capital. In the mid-1990s, for example, Margaret Blair made the case for assessing the economic value of corporations in relation both to financial as well as human capital [24, 25]. Since the 1990s a number of international organizations like Social Accountability International, CERES, the United Nations Environmental Program, the UN’s Global Compact, and the World Bank have developed multi-dimensional performance standards. These in turn have been used by thousands of businesses to evaluate in measurable terms the ways their operations add to or reduce economic values in relation not only to finance but also to workers and natural environments [26, 27]. Robert Eccles in particular has worked at developing practical measures for gauging the ways and degrees business add to or reduce economic value, broadly gauged, by their operations [28]. An increasing number of firms are now undertaking assessment of the non-financial ways businesses add to or erode economics values in relation to environmental, social and good governance standards (ESG). One of the most widely utilized method for assessing the overall ways business augment and erode economic value is that developed by the International Integrated Reporting Council (IIRC), which began its operation in 2011 [29]. The IIRC calls for business to undertake their regular accounting in relation to their utilization of six different forms of capital: namely, financial, manufactured, intellectual, human, social and relationship, and natural [13].
\nThus far I have argued the business of businesses, as complex multi-dimensional organizations, lies in their productive capacity to add economic value to societies in multiple ways. I have observed the progress that has been made in the efforts to measure both the added economic values beyond financial values as well as the costs incurred in the process. If the current operations of business enterprises are to be less closely connected with the adverse environmental, social, and economic trends discussed earlier in this essay, then businesses must do more than measuring their performances in keeping with integrated accounting standards. They must also consider reforming their systems of governance -- that is, the way they deliberate and make authoritative decisions. The operations of many businesses have occasioned these adverse outcomes not only because they tended to measure their goals and costs largely in financial terms but also because characteristically decision-making processes were structured to assign greatest authority to those representing financial interests.
\nIf we hope to encourage business enterprises to foster productivity, rightly understood, in ways that both benefit the enterprises as a whole as well as the larger society, and fittingly benefits all relevant stakeholders, we must consider reforms in governance practices of firms as well as legal changes that will create corresponding legal incentives.
\nThe basic responsibility of businesses is to add economic value to society by making the most productive use of natural and human resources in relation to their particular purposes as particular kind of enterprises. To that end, governing processes must be structured and operate to protect and enhance the wellbeing of the enterprise as a whole. No particular group or constituency should be so positioned that it exercises undue influence in pursuit of its own interests. Accordingly, in recent years many of the initiatives aimed at reforming the governance practices of businesses have aimed at limiting the self-serving actions of senior executives [30, 31, 32]. Williamson warned about the dangers of opportunism and bureaucratization that occurred when governing boards failed to monitor and restrain the agendas of particular groups within the larger organization [33]. It is possible to point to examples, both actual and feared, where other particular stakeholders have exercised – or might exercise--excessive influence over authoritative decision-making within business enterprises. For example, many defenders of neo-liberal economics, while defending the financial model, have worried about the excessive influence of government regulators. They have feared – I think, excessively -- that regulations imposed by governments in pursuit of distant goals like the reduction of greenhouse gases or corporate social responsibility might undermine the productivity of businesses in ways that would be costly to businesses and society and especially to financial interests of investors. At times, many business people have felt that trade unions might exercise disproportionate power over particular companies and industries in ways that both limited their capacities to realize their purposes and reduced their productivity. A case can be made that some huge enterprises have in practice acted like monopsonies with respect to their suppliers, setting strict limits on the prices they pay for purchases, in the process excessively limiting the productivity and, thereby, aggravating working conditions of the latter. In a book titled Permanently Failing Organizations, Meyer and Zucker studied a number of organizations that consumed greater value of resources than the values they generated but remained in business because in an unbalanced way they served the interests of particular stakeholders, in the case of their studies, community groups, employees, and consumers [34]. Accordingly, while recognizing the possibilities of imbalance caused by privileging particular stakeholders, boards ought to be structured and engage in their deliberations in ways that promote the good of the organization as a whole rather than any particular stakeholders.
\nIn order to oversee and promote the wellbeing of enterprises as a whole, governing boards must be structured so that their self-interest as boards aligns with that objective. At present many governing boards operate primarily to promote a financially articulated agenda that especially functions to promote the interests of investors and owners. The financial model primarily regards business enterprises as property belonging to investors and owners, who as they seek to maximize the financial value of firms will, these supporters claim, promote the wellbeing of the enterprise as a whole. We know in fact that does not always happen. Most investors act primarily not as shared proprietors but as consumers of equities. As I have observed, following the financial model, governing boards have often acted in ways that aggravated environmental problems, reduced employment opportunities, and exacerbated wealth inequalities. In order better to promote the overall wellbeing of enterprises as a whole, governing boards must include among their members individuals who are both well acquainted with activities and interests of diverse stakeholders and committed to promoting the value of the enterprise as a whole. In order to realize this goal, most governing boards of business enterprises in Japan and Continental Europe have often included representatives from employees, creditors, community groups, as well as investors [35]. I think a case can be made that it might not be in the best interest of the enterprise as whole for board members to be formal representative of – and primarily answerable to -- diverse stakeholders. Such arrangements might significantly add to governing costs and render boards less focused on protecting and enhancing overall productivity and more given over to wrangles about benefits and costs assigned to particular constituencies [36]. Instead, several steps can be taken so that governing board members exercise the fiduciary loyalty to the enterprise as a whole and their legal responsibilities for due diligence and due care of enterprise resources while fairly respecting the interests of their several stakeholders [24, 37]. Accordingly, while still appointing their own members, governing boards can select individuals who are themselves members of particular constituencies and well-informed with respect to their concerns and interests. Governing boards should also have access to staff who can on an ongoing basis monitor the interactions with stakeholders so the boards remain well-informed.
\nAs I noted at the outset, we live in a business civilization. Governments have extended to businesses a license to operate for several reasons, including especially the productive capacities of businesses to add economic value to society in multiple ways. Over the years, governments have taken steps to protect and promote the productivity of business enterprises in many ways. They have established laws identifying and protecting diverse forms of property, contractual relations, currencies, as well as reliable systems of credit. They have funded and arranged for the development of physical, social, and economic infrastructures, good for societies as a whole and also necessary for business operations to develop and grow. They have used their good offices to facilitate trade. They have both developed system of education, so businesses can hire competent workers, and social insurance schemes to help workers who can no longer work. In order for business enterprises in the contemporary world to maintain their productivity, and thereby add greater value than they erode, it has been and it will continue to be necessary for governments to take appropriate actions. For example, in order to reduce GHG emissions, it has been necessary and useful for governments to institute carbon taxes and offer subsidies and tax credits to encourage the development of alternative sources of energy. In order for them to remain competitive and to keep retail food prices from excessively climbing, in some areas governments have already demonstrated their willingness to offer subsidies and tax credits for some agricultural businesses. Given the seriousness of the climate crisis, many observers think much more must be done to address these problems. In order to foster lively and open competition, it has been necessary and useful for governments from time to time to reduce the monopolistic influence of particular firms within specific industries. These measures have functioned in small ways to limit factors which otherwise would have acted to aggravate inequalities in wealth and economic power. Given the dominance of several firms in the information system sector, many people feel government action is long overdue to foster more lively competition in these industries. With these examples in mind, we can see that there is much evidence that publics have supported governments when the latter have taken actions affecting business activities in order to further societal purposes, to facilitate productivity broadly understood, and limit the adverse effects of particular business practices. In the following paragraphs I propose a number of additional actions governments might take so that businesses operate productively to promote the wellbeing of their enterprises as a whole, limit or reduce their adverse impacts, and thereby maximize the value they add to society.
\nWith respect to overall governance of business enterprises, just as governments (or their agencies) require business to conduct annual financial audits, so they should also be required as well to undertake annual audits of the costs incurred and values added with respect to their uses of natural resources, including air and water, and their uses of human and social capital. So that governing boards are well-informed, some governments now require these kinds of audits. Further along and in keeping with comments I have already made, I will elaborate on the fitting metrics for assessing productivity with respect to labor, viewed not from a financial perspective as is usually done today but regarding human and social assets as intrinsically valuable. Also, with respect to governance of enterprises, a strong case can be made for following the examples of countries like Germany and Japan and require that the governing boards broaden their membership to include people who are well able to know and represent the interests and concerns of the most strategically important stakeholder groups, such as, for example, employees, major suppliers, relevant environmentally oriented groups, creditors, and government agencies.
\nWith regard to efforts to foster responsible environmental practices by businesses, governments have established a number of relevant initiatives in addition to subsidies and tax credits for developing alternative sources of energy and taxes on carbon emissions to reduce GHG emissions. Many governments have been taxing or fining businesses for excess water pollution. Because all businesses involved in extracting non-renewable resources are depleting valuable resources, some countries like Norway are effectively taxing these operations in order to establish huge public funds that can in turn be used to further other public purposes.
\nFor some time many governments have de facto recognized that dysfunctions in labor markets. They have, accordingly, established minimum wage standards as well as employment offices to help enterprises find suitable employees and worker find positions of employment. Partly in response to the expansion in the use of temporary workers, some government, like the United States, offer payments in the form of tax credit to workers whose annual income falls below recognized poverty lines. This has become a huge public transfer program that functions to reinforce the practices of many businesses to hire workers part time and/or part year rather than full time. Given the slow but steady replacement of workers by smart technology, governments face in the future several options. They will be forced either to expand these kinds of tax credit programs; develop some form of basic income initiatives; re-establish the kind of employment generating programs like the Public Works Administration, the Works Progress Administration, and the Community Conservation Corp that were so effective in the United States during the 1930s; and/or they must think seriously about initiatives that would foster greater employment within existing businesses.
\nBecause in this essay I am calling for a re-thinking of the business of business, I will elaborate on the last alternative. The United State government has spent hundreds of billions of dollars supporting the housing industry and related employment opportunities by means of tax credits for mortgage costs. Correspondingly, I think governments must now consider initiatives that would operate to retain or expand employment opportunities in business enterprises in general. Basic to these initiatives would be a re-thinking of productivity and labor, not from a financial perspective but, from the perspective of all working age adults seeking remunerative employment opportunities and the vast and valuable stock of human capital they represent. Accordingly, finding feasible ways for businesses to retain useful workers and to expand the hours of employment would be regarded as fostering forms of productivity associated with uses of human labor. During slow periods, business enterprises might direct some of their employed workers to invest greater amounts of time learning and upgrading their skills, exploring new lines of business activity, and/or engaging in community projects. Because adding these hours of employment would in turn represent added costs to enterprises, then governments in recognition might be called upon proportionately to reduce business taxes and/or offer tax credits. These added costs to governments would in turn be balanced by reduced costs for programs like employment tax credits and unemployment insurance. This kind of initiative would be in the interest both of enhancing wellbeing of workers as well as enterprises as a whole.
\nWe must also consider what kinds of initiatives governments might take to reduce the way current business practices tend to aggravate inequalities in wealth. I am not at this point proposing particular initiatives. Rather, I refer to several actions that might be taken in order to indicate that possibilities for re-thinking the purposes of business enterprises with respect to their influence on aggravated inequalities in wealth that do exist. Obviously, the kind of government incentives just discussed to encourage businesses to retain workers, hire more employees full time rather than part time, and expand employment hours might indirectly function to influence firms to decrease the share of business earnings allocated to reward investors and increase the share used for labor expenses. At the same time, if governments increase the tax rates for the highest incomes and introduce even small taxes on wealth, then business might be less inclined to use their earnings to increase executive stipends and returns on investors, knowing that a significant portion of these increases will be taxed. Clearly, if the governance practices are altered to represent better the interests of stakeholders other than investors, then it is more likely that earnings of businesses will be more broadly distributed to the advantage all stakeholders in ways that both serve the interests of enterprises as a whole and benefit particular stakeholders proportionate to contributions they make and the risks to which they are exposed.
\nIn conclusion, currently many businesses are operating in ways that have had adverse outcomes on natural environments, employment opportunities, and aggravated inequalities in wealth. These adverse consequences occur to a significant degree because many businesses are operated and organized in order to maximize the value of businesses measured almost exclusively in financial terms, thereby prioritizing financial interests above all other interests. The financial model of business enterprises has become so dominant that many ESG initiatives are promoted and defended as being financially advantageous to businesses rather than because they will provides means for increasing the productivity of enterprises with regard to natural and human resources valued on their own terms as valued economic assets. I have criticized the financial model for a number of reasons. In so far as businesses have operated in keeping with this model, they have tended to occasion the adverse environmental, social, and economic consequences described above. This model provides an overly narrow and restricted understanding of productivity and has encouraged businesses disproportionately to favor the interests of investors over other stakeholders.
\nI have called for significant changes in how to think about the business of businesses and how business enterprises govern themselves. Many people have a vested interest in the financial model of business enterprises and will resist these changes. As the climate crisis becomes more severe, many people will probably be forced to modify their views modestly and work to reduce GHG emissions, while still prioritizing their financial interests. The proposed changes, like those endorsed by the Business Roundtable, that recognize business enterprises in relation to their stakeholders are likely to meet with resistance. Nevertheless, a number of these changes have already been introduced, in this or that country, in this or that firm, and defended by business people both because they respect the complex, interactive character of business enterprises as they operate in practice and because they more adequately foster and gauge productivity – not as currently almost exclusively in relation to financial returns but in the effective and value-added utilization of natural and human resources to meet human needs and wants. After all, that is what the business of business is all about.
\n\n
I initially developed this line of analysis in an essay on corporate governance, published in 2001 [38]. For typical expressions of Symbolic Interaction, see the writings of Anselm Strauss [39] and Irving Goffman [40, 41].
This view of stakeholders is more limited than that proposed by Freeman and many others, who define stakeholders broadly in relation to any group influenced by or in a position to influence the activities of business enterprises [42, 43]. I think we ought to restrict which groups count as stakeholders to those who can, on the basis of law, contractual arrangements, customary practices, or changing political realities, make legitimate claims on business enterprises.
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