Mechanical and geometric data for each tested panel.
--\x3e of full-height wall segments and inversely proportional to the openings height;
\nFrom Eqs. (1) and (2), the ratio between PA and PB is equal to the ratio between αA and αB:
\nThe beams above and below the opening contribute in transferring load;
All the panels have the same height and similar openings.
Therefore, the following analytical formulation is proposed:\nwhere b and h are, respectively, the width and the height of the openings, while L is the width of the panel (Figure 9). P is the maximum shear strength attained by each panel during the experimental tests with the exception of panel D, whose value is not the one given by the experiment but the one corresponding to a deformation of 30 mm that, looking at the P-δ curve (Figure 8), and comparing its behaviour with the other three panels, seems more reliable.
\nSymbols for the formulation of the ultimate strength in the analytical model.
The geometrical dimensions for the tested panels are reported in Table 3. Table 4 shows the application of the proposed analytical expression for the four panels that have been tested in Tsukuba. The ratio between the ultimate strength of two panels determined during the experimental session is compared with the value obtained by comparing the geometrical conditions.
\nSpecimen | \nP (kN) | \nL (m) | \nb (m) | \nh (m) | \n\n |
---|---|---|---|---|---|
One opening | \n1S4-A | \n112.42 | \n4 | \n2 | \n2.2 | \n
1S4-B | \n167.90 | \n4 | \n2 | \n1.4 | \n|
Two openings | \n1S6-C | \n160.64 | \n6 | \n3.6 | \n2.2 | \n
1S6-D | \n272.05 | \n6 | \n3.6 | \n1.4 | \n
Mechanical and geometric data for each tested panel.
Application of the proposed formulation and errors between the analytical values and the experimental value.
The error given by the analytical value never exceeds 8%, showing therefore that the mathematical formulation can predict fairly closely the ultimate strength of panels with the same geometry, characteristics and boundary conditions. However, it must be noted that this relationship gives acceptable results when panels are similar. If configuration of the openings or dimensions of the compared panels such as height and thickness change and, for example, the openings are not symmetrical, the proposed equation is too simple and it will not lead to reliable results.
\nMoreover, no tests on no-fenestrated panels have been conducted, so it was not possible to compare the results with a common value Pf. Thus, the analytical formulation can be used only if the ultimate strength of one of two panels is already known and the panels have the same height. The mathematical model proposed in this paragraph is based on rough calculations and is therefore very approximate; however, it can be interpreted as a way to provide first information about the tendency of the reduction of racking strength of CLT shear walls with openings.
\n\nThe tested panels were modelled in SAP2000 by using a two-dimensional (2D) schematization with “Shell-Layered/Nonlinear” model [16]. The material properties adopted in the finite element model are listed in Table 5.
Modulus of elasticity—lower value (N/mm2) | \nElow | \n4200 | \n
---|---|---|
MOE—average value (N/mm2) | \nEav | \n5200 | \n
Maximum bending strength (N/mm2) | \nσb | \n11,6 | \n
Modulus of elasticity—outer layers (N/mm20) | \nE1 = E3 = Eh | \n173.33 | \n
Modulus of elasticity—inner layer (N/mm2) | \nE2 = Ev | \n5200 | \n
Rolling shear modulus (N/mm2) | \nG12 = G23 | \n100 | \n
Longitudinal shear modulus (N/mm2) | \nG13 | \n400 | \n
Tensile strength—minimum value (N/mm2) | \n6.1.1. σt | \n12 | \n
Tensile strength—average value (N/mm2) | \nσt | \n16 | \n
Density (kg/m3) | \nρ | \n439 | \n
Poisson’s coefficients | \nν | \n0.35 | \n
Material properties adopted in the finite element model.
Under lateral loads, the connectors exhibit two different mechanisms of deformation. In the vertical direction, the anchors are subjected to tension, while in the horizontal one they experience shear deformation. These two deformation mechanisms are incorporated into the model by using individual springs for each of it, which act in unison. To find the stiffness and ultimate strength, tests on single-anchor elements should be conducted. In the present case, only the tensile connector (UT) has been previously subjected to monotonic load tests to correctly define its behaviour when subjected to tension.
\nThe stiffness, strength and ductility of the steel connections are determined according to the Yasumura and Kawai procedure [17]. This procedure was initially proposed for the evaluation of wood-framed shear walls. The ultimate strength Pu is calculated so that the equivalence of the deformation energies is achieved by assuming an elasto-plastic load-displacement curve. Figure 10 shows the definition of the bilinear curve that schematizes the behaviour of the tensile connectors. The contact—valid for tensile connectors—has been explicitly modelled using a set of compression-only springs identified at each point of the boundary mesh. For simulating the presence of the steel foundation, nodes with centre-to-centre distance of 10 cm have been generated at the base of the wall and all the degrees of freedom have been constrained. In the wall-to-floor contact, zero-length multilinear springs connect the nodes of the wall panel to the floor nodes. The compression-only springs are stiff in compression, and allow free movements away from it when subjected to tension. These springs are distributed along the contact between the wall and the floor. The friction between the steel beam foundation and the timber wall element is described by using spring elements with symmetrical and rigid-plastic behaviour placed along the whole length of the lower edge of the panel between the foundation nodes and the panel. The sliding resistance is described by the following equation:
\nwhere FN is the axial force at the current analysis step, kf the static friction coefficient and Ff is the static friction force. The friction coefficient between the rough concrete and the CLT wooden surface was estimated as equal to 0.7 instead of the usual value of 0.4 used for two pieces of timber. In a proper schematization of the panel, the friction force should be calculated for each node taking into account the effective axial force that lies on each spring. Springs are stiff until the shear flow in the contact zone does not attain the estimated friction force. After this stage, friction springs have constant load-bearing capacity and resist sliding of panel in combination with non-linear springs that represent shear connectors.
Definition of the bilinear curve (kN-mm) determined according to the Yasumura and Kawai procedure [17].
A pushover analysis was performed with a control of imposed displacement.
\nConfirming the experimental observation, the break occurs in the inner-cross layer due to the maximum tension attained in the corner of the opening of panel A (Figure 11). The maximum strength of 12 MPa is attained for a corresponding displacement of 17mm and 83-kN force.
Panel A: (a) maximum and minimum tension stresses in MPa at the last analysis step; (b) numerical pushover curve compared to the experimental curve.
The force-deformation response obtained matches quite good to the experimental response for the elastic behaviour. When the panel starts to break and the behaviour became plastic, the CLT shear wall is subjected to large displacement for small increments of load.
\nFor panel B, the upper left corner is the one where the break occurred, as seen in the experimental test (Figure 12a). Figure 12b shows the pushover curve obtained for the shear wall B. Panel B, contrary to panel A, has a very brittle behaviour. In this case, the yielding point is near the breaking point and an overall acceptable accuracy in terms of elastic stiffness was obtained. The presence of the sub-window increases the global stiffness of the panel and highlights again the relevant role of the boundary conditions (contact and friction). The overall behaviour of panel C, due to the absence of the sub-windows, depends strongly from the UT and US connectors.
\nIn this case, the maximum tension is concentrated in both the external and internal corners as shown in Figure 13a. Due to the eccentric position of the load joint (located not in the geometrical centre of the panel but in the centre of the right window), the maximum tension that brought to failure occurred in the inner corner. Figure 13b shows the comparison between the backbone curve and the pushover curve with the observation that the numerical model results approximate the experimental ones quite well.
Panel B: (a) maximum and minimum tension stresses in MPa at the last analysis step; (b) numerical pushover curve compared to the experimental curve.
Panel C: (a) maximum and minimum tension stresses in MPa at the last analysis step; (b) numerical pushover curve compared to the experimental curve.
As shown in Figure 14a, the stress concentration occurs in the corners of the windows and the breaking point corresponds with the inner corner of the left window confirming the experimental results. Also in this case, the sub-window contributes to increase the overall stiffness behaviour. In contrast with the other cases, for panel D, the pushover curve does not approximate exactly the stiffness of the panel (Figure 14b). The main reason of this result can be founded both in the general errors that occurred in the experimental session and in the general approximation of the boundary conditions. Other numerical analyses could be aimed at evaluating the energy dissipated by panels during cycles as done for masonry buildings [18].
Panel D: (a) maximum and minimum tension stresses in MPa at the last analysis step; (b) numerical pushover curve compared to the experimental curve.
The main results obtained from experimental tests on CLT panels with openings have been compared and interpreted through analytical and numerical models. Concerning the experimental tests, failure occurred at the upper corner of the opening for all the specimens. The general behaviour was brittle for all the panels with the exception of the panel with a one-door opening, the most ductile and also the one with maximum dissipation of energy and deformation. The maximum strength was obtained for the sample with two windows but in this case the bending and sliding of the panel affected the results. Anyway, the maximum strength of the window type (panels B and D) was observed to be higher than that for the door type (panels A and C). An analytical model was adopted to predict the ultimate strength of panels similar to the tested ones, knowing the ultimate strength of one of two panels and the panels have the same height. The error given by the analytical method never exceeded 8%, showing therefore that the mathematical formulation can predict fairly closely the ultimate strength of panels with the same geometry, characteristics and boundary conditions. Finite element models confirmed, in terms of failure type and crack position, the experimental results. Moreover, the pushover curve obtained from the finite element procedure generally matched the experimental one quite well. Further analyses could be addressed to evaluate the out-of-plane resistance of the timber panels, by means of rocking analysis with proper boundary conditions, applying analogous concepts adopted for masonry panels [19, 20].
\nAn experimental campaign aimed at evaluating the ultimate behaviour of CLT panels with openings was here described and interpreted with both analytical and numerical models. The four-wall panels were shown to exhibit a prevalent brittle behaviour, except for the specimen with one-door opening, more ductile. This response was reproduced quite well in the multilayered finite element model. The position of the cracks at the ultimate limit state was correctly obtained from the numerical procedure, highlighting that the failure occurs at the corner of the openings, in different position depending on their size and configurations. The analytical model was capable to correctly evaluate the values of ultimate limit strength of walls with cut-out openings, with errors lower than 8%.
\nThe research presented in this paper was funded by the Japanese company ‘Nihon Sekkei System’ and supported by PRA2016 funding of the University of Pisa.
\nThe authors would like to thank the Timber Structure Laboratory members (Department of Human and Social System, Institute of Industrial Science of the University of Tokyo) and Prof. Massimo Fragiacomo who provided technical expertise for the experimental testing.
\nNowadays, organizations are facing a lot of challenges when competing in various sectors of the global market such as economics, technology, and labor. One of the crucial strategies for an organization to gain competitive advantage is exploitation of training. In particular, training is an important function for an organization to cultivate employees’ explicit and implicit knowledge, skills, and abilities and transfer employees into the valuable resources of an organization. This function is not only linked to improvement of business performance but also an effective determinant in shaping employee attitudes, which are critical variables to influence job performance [1]. According to the literature, job satisfaction is defined as “a pleasurable emotional state resulting from the appraisal of one’s job or job experiences” ([2], p. 94). It is one of the major job attitudes to affect employees’ behaviors and shows a strong relationship with other affective outcomes such as learning motivation, turnover rate, and firm performance [3].
\nSince training and job satisfaction are two important variables which individually produces impacts on firm performance, this chapter aims to elaborate training in organization toward job satisfaction. This chapter is organized in four sections. The first section describes how to plan and carry out an effective training program. It begins by discussing the definition of training and the meaning of learning. Next, a training effectiveness model is constructed to present a whole picture about the factors which influence the training outcomes. Elucidation will be provided for each part of the model which includes individual characteristics, organizational characteristics, and task characteristics, followed by needs assessment, training design, and training evaluation. The second section focuses on job satisfaction in which the fundamental concepts are introduced. This is followed by discussion of the impacts of job satisfaction on job performance. The third section describes job training satisfaction and how it contributes to job satisfaction, job performance, and other work-related attitudes. The final section is Conclusions.
\nWhat is training? Training refers to “a planned effort by a company to facilitate employees’ learning of job-related competencies” ([4], p. 5). It is also defined as “a planned and systematic effort to modify or develop knowledge, skills and attitudes through learning experiences to achieve effective performance in an activity or a range of activities” ([5], p. 41). Training is the major means to be used by organizations to cultivate employee competence to reach the appropriate required levels. It is also an important business strategy for organizations to cope with a variety of forces affecting the workplace [6, 7]. It is stated that training is organized and used by an organization as a business strategy to help employees develop and acquire competence, which includes knowledge, skills, behaviors, and attitudes that are critical for successful job performance. Typically, training can be distinguished by two basic types of locations where it is conducted, i.e., off-the-job and on-the-job. Off-the-job training provides learning opportunities on a variety of topics at a site other than where the work is actually done, whereas on-the-job training (OJT) occurs in the work setting itself [6]. With the assistance of modern technology, online training can be realized as well [8]. No matter which sites or ways the training is conducted, the key to effective training is to activate learning to occur.
\nIn most of the textbooks, learning is defined as an effect of experience on behavior [9]. It is related to a process of change in behavior that is due to experience. Actually, all learning involves two processes: one is an external interaction process between the learner and his or her social, cultural, and material environment, and the other is an internal psychological process of elaboration and acquisition in which new impulses are connected with the results of prior learning [10]. However, if the outputs of learning process (either through external or internal) only produce change in people’s behavior, such a definition cannot be satisfied by many researchers [9]. Therefore, learning has also been defined as “a relatively permanent change in human capabilities that is not a result of growth processes” ([4], p. 140). Based on this definition, learning can bring out three different outcomes. The first one is the content dimension, which refers to knowledge, understanding, skills, abilities, and attitudes. The second one is the incentive dimension which includes emotion, feelings, motivation, and volition. The final one is the social dimension, which involves interaction, communication, and cooperation [10]. Learning, thus, can be further referred to as a process that is “seen” through changes in knowledge, skills, attitudes, behaviors, emotion managing ability, communication style, and more during training and generalization to the transfer context.
\nTraditionally, in the workplace, learning occurs through formal training and development. All formal learning activities are designed with specific learning objectives to cultivate employees in lifelong processes for ongoing development and acquisition of competencies to meet the challenges that the organization faces from its internal and external environment [8]. Typically, such learning is activated through direct instruction, which engage learners in lectures, discussions, simulations, role-plays, and other structured activities [11]. With technological advancement and intense competition, training scholars have claimed that employees must extend their learning outside the formal classroom or work settings to ensure competencies are maximized [12]. Thus, informal learning becomes important because it represents the most part of learning occurring in organizations. Watkins and Marsick characterized informal learning as a process “based on learning from experience, embedded in the organizational context, oriented to a focus on action; governed by non-routine conditions; concerned with tacit dimensions that must be made explicit; delimited by the nature of the task, the way in which the problems are framed, and the work capacity of the individual underlying the task; and enhanced by proactivity, critical reflectivity, and creativity” ([13], p. 287). It is unstructured and occurs outside a learning institution [11].
\n\nFigure 1 shows the relationships between training and learning. Training, either off-the-job, on-the-job, or online, involves transferring expertise and knowledge from experts who have it to novices who need it [14]. Both training and learning activities consist of a process of knowledge sharing, which is an element of reciprocity and is a giving-taking exchange process of information or assistance to others [15]. Knowledge sharing between employees and across teams allows an organization to exploit existing knowledge-based resources and has been identified as a positive force in creating innovative organizations [15–17].
\nThe relationships between training and learning.
In a competitive environment, while employee training and learning have become an increasingly important strategic issue for organizations [8], the core concern is how to help the company and trainees receive benefits from the training activities? The related questions include “what kind of factors that may affect the success and effectiveness of training” and “what/how trainers can do to make training program effective?” Training effectiveness, according to Noe ([4], p. 216), refers to “the benefits that the company and trainees receive from training.” It focuses on understanding the whole learning system to determine why learners learn or do not. It also explains why the learning results happen and assists training designers to make troubleshooting to improve training [18]. Thus, theoretically, training effectiveness is the study of the individual, training, and organizational characteristics that influence the training process before, during, and after training [18]. Training effectiveness differs from the training evaluation. Training effectiveness is a theoretical approach to understand learning outcomes, whereas training evaluation is a methodological approach to measure these learning outcomes [18]. A summarized model of training effectiveness is presented in Figure 2 [19]. Figure 2 shows the factors that impact the training outcomes and job performance and the relationships between them. Three major topics will be discussed, that is, needs assessment before training (shaded with gray color), program design and delivery during training (shaded with orange color), and training evaluation after training (shaded with pink color).
\nThe comprehensive model of training effectiveness.
Effective training practices involving the use of a training design process begin with a needs assessment [4, 8, 18]. A need is a measureable gap between two conditions—what currently is and what should be [20]. In order to define the gap of need in training, a complete assessment process should be conducted to figure out problem areas, issues, or difficulties that should be resolved [20]. Thus, a training needs assessment refers to the process used to determine whether training is necessary and why specific training activities are required [4, 8]. In most contexts, a needs assessment focuses on gaps rather than solutions [20]. Theoretically, it involves three levels of analysis: organizational analysis, person analysis, and task analysis. Organizational characteristics, individual characteristics, and task characteristics are factors to be considered for three levels of analysis in the beginning of training design. The purpose of these levels of analysis is to realize the gaps in current training programs and further to collect information for program design and problem-solving [4, 8].
\nIn Figure 2, the first factor is organizational characteristics. Organizational characteristics include organizational structure, business strategies, support of managers for training activities, training resources, organizational procedures, reward systems, culture, and climate [4, 8, 18, 21]. Each variable plays a very critical role to impact training effectiveness. For example, Facteau et al. [22] found that intrinsic and compliance incentives, organizational commitment, and social support for training are able to predict trainees’ pretraining motivation. Motivation is the key determinant of the choices individuals make to engage in, attend to, and persist in learning activities, which will affect learning performance [3]. Because organizational analysis is concerned with identifying whether (1) training fits the company’s strategic objectives; (2) training supports the company’s culture, climate, and policies; and (3) the company has the budget, time, and expertise to carry out training, this analysis is usually conducted in the first place [4]. Several major questions will be assessed in this analysis: “How does the training relate to business objectives?” “How does training support business strategy?” “What are the threats to the talent base?” “How does the training impact day-to-day workplace dynamics?” “What are the costs and expected benefits of the training?” [4, 8].
\nAnother factor, individual characteristics, includes cognitive ability, attitudes, locus of control, personality, anxiety, age, self-efficacy, expectations, job involvement, pretraining motivation, need for achievement, independence, and more [18, 19, 23]. A large number of studies have been demonstrating how individual differences influence transfer of learning and learning performance, which further impacts on training effectiveness [7, 24]. For example, Noe showed that individuals with an internal locus of control had more positive attitudes toward training since they viewed training as a means to help them receive tangible benefits [25]. Mathieu et al. proposed that trainees with high achievement motivation were more motivated to learn and perform well in the training program [26]. Klein et al. found that the learners with high learning goal orientation (LGO) would be significantly related to the factor of motivation to learn [27]. Macey and Schneider claimed that four individual characteristics like positive affectivity, proactive personality, conscientiousness, and autotelic personality were more likely to have greater psychological availability to learn and also perceived learning activities being more meaningful such that they are likely to participate actively in the training activities [28]. In addition, many researches have suggested that learning is negatively related to aging [24]. Also, three of the big five factors—conscientiousness, neuroticism (emotional stability), and openness to experience—significantly impact learning, training, and transfer outcomes [29]. Since employees’ individual characteristics make huge impacts on learning performance, personal analysis helps to identify employees’ characteristics and readiness for training and recognize who needs training and who will perform well in the training program.
\nThe third factor, task characteristics, consists of the knowledge, skills, and abilities required to complete the tasks, the equipment, and environment that the employee works in, time constraints for a task, safety considerations, or performance standards [4]. Thus, for task-level assessment, it involves checking specific duties and responsibilities assigned to various jobs and the types of skills and knowledge needed to perform each task [8]. In other words, the major purpose of task analysis is to collect job-related information to identify the task and the training that employees will require in terms knowledge, skills, and abilities. This analysis should be conducted only after the organizational analysis because it is a time-consuming process to gather and summarize data from persons in different layers of the company [4]. Several questions will be addressed in this analysis. For example, what kinds of responsibilities are to be assigned to the job? What are the skills or knowledge needed for successful performance? What are the implications of mistakes? What tasks should employees be trained [4, 8]?
\nAfter identifying the gaps and training objectives through the needs assessment, the next step is the design and delivery of the training itself [8]. Program design is rooted in learning theories and refers to “the organization and coordination of the training program” ([4], p. 172). More specifically, “it is a process for helping to create effective training in an efficient manner. It is a system that helps designers ask the right questions, make the right decision, and produce a useful and useable product as the situation requires and allows” [30]. Thus, the purpose of a program design is to make learning occur and training effective. Research has indicated that each element of training design process is related to the quality of training. Researchers such as Baldwin et al. and Klein et al. presented that training design with organizational characteristics and individual characteristics together influences trainees’ motivation to learn and, motivation to transfer, and real training transfer [27, 31]. Latif presented a model of training effectiveness which points out that training satisfaction comes from trainees’ feeling of satisfaction with training session, training content, trainers, and learning transfer [1]. Noe et al. also showed that technology-based and face-to-face learning methods and contextual factors such as organizational climate, interpersonal dynamics, and individual differences are able to promote psychological engagement in learning, which is a crucial factor to enhance the effectiveness of training, development, and related learning activities [7].
\nTraining methodology was also found to be an important factor in the equation of job training satisfaction [32]. Compared to other training methods, on-the-job training is one of the oldest, most widely used training methods in the workplace. It can be useful for training newly hired employees, orienting promoted or transferred employees to the new job positions, upgrading employees’ competencies when new technology is used, and delivering cross-culture training to employees who are assigned to work overseas [4]. Since OJT occurs at or near the workplace using actual equipment and tools, most of the time, trainees are highly motivated to learn and can be customized to the experiences and abilities [4]. Although there are many advantages, OJT is informal or unstructured in nature and has received serious criticism such as incomplete and unpredictable [33]. Thus, structured on-the-job training (S-OJT) was proposed by Jacobs and McGiffin [34]. In contrast to informal and unstructured OJT, structured OJT adopts a planned approach to train and develop employees’ competencies [33]. Many research results indicated that S-OJT is superior to unstructured on-the-job training in terms of having lower training cost, enhancing skills acquisition, and removing learning anxieties [6].
\nIn the past, a large portion of the research in program design has paid great attention to traditional instructional design (ISD) model, which includes conducting a needs assessment, setting the objectives of training, identifying evaluation criteria, selecting appropriate trainers and training methods, making meaningful materials, and properly coordinating and arranging training delivery. In addition, it involves ensuring training transfer, offering a good training site, and providing opportunities for practice and feedback [4, 7]. Although the traditional instructional design brings a lot of benefits to enhance training effectiveness, it is more instructor-oriented where lecture proceeds with adding sophisticated elements and feedback loop with interaction and communication [35]. Some scholars have recently claimed that instructor-oriented design is deemed to be disadvantageous for effective learning. They argued that the learners in instructor-centered program may be passive in learning activities and seldom grasp the significance or realize the intricacies of the model from the instructors during the training [16, 35]. Thus, it has been claimed that the instructional design model needs to be modified or adapted to better fit the learner-centered learning, particularly technology-based learning [16, 36].
\nWhat is learner-centered learning? Learner-centered learning involves the balance between instructor and learner shifting the roles, so that the learners take on the responsibility to learn and the instructor becomes more of a facilitator [37, 38]. In this learning paradigm, instead of transferring factual knowledge to the learners, the instructor focuses more on creating a learning environment and providing learning opportunities that empower learners to construct knowledge for themselves [39]. Attention, in this paradigm, is given not only to what the learners learn but also to how they learn and whether they are able to retain and apply the knowledge or not [36]. More specifically, the instructor with the role of facilitator utilizes multiple teaching methods beyond traditional lecturing to help the learners actively participate in learning [35].
\nThus, several tips for delivering the training with the learner-centered approach are described as follows [36]. First, at the beginning of the training, the trainer involves learners into decision-making process for choosing the course textbook. Second, after choosing the textbooks, the trainer invites learners to pick up the topics which they are interested in and also fit personal needs. In this way, the learners would take responsibility for learning by themselves. Third, the class will be run like a discussion session. The trainer gives training materials before the class and asks them to read in advance. Following the Shor’s suggestion that the trainer controls his/her “authoritative academic voice” [40], the trainer says as little as necessary and focuses on determining what they are interested in, what they have troubles with and what they want to talk about. The trainer offers questions, comments, structures, and academic knowledge while patiently listening to trainees’ thoughts and ideas. The trainer and the learners learn from each other through interaction. Fourth, Weimer suggested that the careful design of assignments which help students effectively use the power they are given is the key component of sharing power to the learners [41]. Thus, the trainer needs to structure the assignments well and allows the trainees to make choices about the ways to complete the projects, for example, by conducting interview or submitting a real lesson activity.
\nThree critical issues must be considered in the designing and delivering stage [8]. The first one is interference. Interference occurs “when prior training, learning, or established habits act as block or obstacle in the learning process” ([8], p. 391). That is, someone who has more experience in behaving in a certain way will have more difficulties in changing the way he/she responds when encountering a situation. Therefore, when designing the training, the trainers need to be aware of this issue. The second one is transfer design [8]. Transfer refers to whether the trainee or learner can actually perform the new skills or use the new knowledge on the job [4]. Transfer design, thus, is defined as the ability to transfer learning to the job and to which the training instruction matches the job requirements [42]. In order to ensure that the organizations are able to receive benefit from training, Lim and Johnson suggested that training design, content, and instructional strategies must be related to the objective of transfer, whether near or far transfer [43]. In other words, transfer mechanisms such as climate for transfer, management and peer support, opportunity to perform, training awareness, and using self-management strategies need to be included in the design of a training program for maximizing transfer [4, 21, 44]. The third one is the needs of adult learners. It is said that the ways of children’s learning are different from those of adults. Several assumptions were proposed by Malcolm Knowles [45]: (1) adults have the need to know why they learn, (2) adults have the need to be self-managed, (3) adults bring more work-related experiences into the learning context than children or teenagers, (4) adults learn with a problem-centered approach, and (5) adults are motivated to learn by getting both extrinsic and intrinsic motivators. Since most of the job-related training is targeted for employees whose age is over 18, the training program must meet the needs of these adult learners in order to enhance training effectiveness.
\nEvaluation is an integral part and the final stage of most instructional design (ID) models [46]. Theoretically, it is a systematic process of collecting data in an effort to measure and determine success or failure of a training program with regard to content and design [18, 47]. Two questions intend to be answered in the evaluation process, that is, whether (1) training objectives are achieved in the learning process and (2) accomplishment of those objectives results in enhanced job performance [48]. Thus, evaluation can be divided into two categories, formative evaluation and summative evaluation [46, 49, 50]. Formative evaluation is an evaluation with the purpose to improve design and development to enhance learning, whereas summative evaluation is intended to determine whether the training program is worthy or effective [51, 52]. Besides, Campbell stressed that the most important and fundamental thing is whether trainees have learned the materials covered in training or not [53].
\nTraditionally, Kirkpatrick’s model was one of the first efforts to create a framework for training evaluation. It is also the simplest method to understand training effectiveness [18, 54]. According to Kirkpatrick, training can be evaluated at four levels. Level 1 is the “reactions” criteria, which evaluates trainees’ affective and attitudinal perceptions to a training program, including facilities, trainers, and content. For the “reactions” criteria, evaluation is performed via a questionnaire completed by trainees or self-reported regarding perceived learning gains [55]. Level 2 is the “learning” criteria, which evaluates the extent to which trainees have learned the training materials covered in training and acquired knowledge, skills, attitudes, and behavior from a training program. Learning outcomes are typically measured by using various forms of knowledge tests such as pencil-and-paper test or by immediate post-training measures of performance and skill demonstration in the training context [56]. Level 3 is the “behavior” criteria. It refers to as transfer criteria and evaluates the extent to which trainees have applied the learned competencies on the job. For behavioral criteria, evaluation is assessed by self-ratings, supervisor ratings, or objective performance indicators [56–58]. Level 4 is the “results” criteria, which evaluates the extent to which the training program has improved business outcomes and to increase organizational-level profits [47]. Although this kind of assessment is the most difficult to be obtained, it is highly desirable for the organizations. Most of the time, “results” are operationalized by productivity gains, reduced costs related to employee turnover, increased customer satisfaction, enhancing employee commitment, or increase in profitability [57, 58].
\nAlthough Kirkpatrick’s framework is the most accepted approach for training evaluation, it has been criticized by many scholars. One of the criticisms is that the criteria used for evaluation in Kirkpatrick’s framework do not relate to the training needs, the learning objectives, and strategic goals of the organizations [4]. The second one is the lack of relationship between reaction, learning, behavior, and results’ criteria [55]. As a result, both training practitioners and academic researchers have developed a more comprehensive model for training criteria. For example, Kraiger et al. attempted to expand the original Kirkpatrick model by linking the learning outcomes with training evaluation [48]. Based on Kraiger et al.’s proposition, three categories of learning outcomes, that is, cognitive, skill-based, and affective outcomes, should be included in evaluation [48, 59]. Specifically, cognitive outcomes are used to determine the degree to which trainees are familiar with principles, facts, techniques, procedures, or processes emphasized in the training program. It includes verbal knowledge, knowledge organization, and cognitive strategies. Skill-based outcomes, including skill learning and skill transfer, are used to assess the level of technical or motor skills and behaviors. Affective outcomes include both attitudinal and motivational change, which also involves disposition, motivation to learn, self-efficacy, tolerance for diversity, safety attitudes, customer service orientation, and goal setting [4, 48].
\nAmong three categories of learning outcomes, affective outcomes have attracted a lot of attentions in different research areas such as education, psychology, and organizational behavior. The scholars are particularly interested in the issue regarding whether self-efficacy or motivation to learn can be changed through training and how different training methods impact self-efficacy and motivation to learn. For example, Gist found that a training method comprising cognitive modeling with practice and reinforcement generated significantly higher participant self-efficacy than a method involving only lecture and practice [60]. Torkzadeh and Dyke suggested that training significantly improved Internet self-efficacy for trainees, both males and females [61]. Combs and Luthans stated that the diversity training enhanced trainees’ diversity self-efficacy [62]. Huang and Jacobs claimed that structured on-the-job training could generate higher self-efficacy to achieve training outcomes than classroom training with lecture only, especially for trainees with lower general self-efficacy (GSE) [63]. Huang and Jao reported that structured on-the-job training could generate higher trainees’ motivation to learn than classroom training [64].
\nAmong thousands of attitudes, job satisfaction is one of important work-related attitudes in the work environment [3]. Specifically, job satisfaction refers to the degree to which the feeling of satisfaction is derived from the employees’ perceptions toward different facets of their tasks or jobs [65, 66]. In other words, job satisfaction is a pleasurable or positive emotional state emerging as the result of appraising one’s job or job experiences and as the fulfillment or gratification of certain needs that are associated with one’s work [3, 67, 68]. Simply put, job satisfaction is the combination of feelings, beliefs, and behavioral intentions that workers hold a relation to their current jobs [3, 69]. The employees’ job satisfaction is measurable and can be changed [3]. A popular way to explain job satisfaction has been the person-environment fit paradigm, which suggests that the more a person’s work environment is fulfilling one’s needs, personality, values, or personal characteristics, the greater the degree of job satisfaction is [70].
\nWhile tackling the issue of job satisfaction, some typical questions were raised by researchers. For example, why are some employees more satisfied than others? What kinds of work tasks are especially satisfying? How to design a task to make employees feel satisfied? Colquitt et al. claimed that values play a key role in explaining job satisfaction [2]. What is value? Values are “the things that people consciously or unconsciously want to seek or attain” ([2], p. 94). Thus, value-percept theory argues that “job satisfaction depends on whether the employee perceives that his or her job supplies the things that he or she values” ([2], p. 94). Based on the value-percept theory, the dissatisfaction of employees can be expressed as follows:
\nwhere Vwant refers to how much of a value an employee wants, Vhave is the value the job supplies, and Vimportance reflects the importance of the value to the employee. It can be seen that, although the difference between Vwant and Vhave causes the dissatisfaction, it is the importance of the value that will either magnify or minimize the dissatisfaction [2]. In the value-percept theory, five specific facets of satisfaction, i.e., pay satisfaction, promotion satisfaction, supervision satisfaction, coworker satisfaction, and satisfaction with the work itself, must be met in order to achieve overall job satisfaction.
\nWhile explaining job satisfaction from the perspective of value-percept theory, personal characteristics make the issue of “the things that each employee wants to pursue and feels important in the workplace” complicated. Personal characteristics include personality disposition, attitudes, self-efficacy, self-esteem, motivation, gender, communication style, emotions, and more [3, 71]. Since each employee is independent and unique, the value of things an employee wants and their importance differ from one to another. Such differences cause the variance in dissatisfaction. Personal characteristics offer the explanation to the question of why some employees are more satisfied than others. Take personality as an example. If the employees’ score is high on the neuroticism scale in a personality measurement, they are likely to carry a rather negative view toward the world. This makes them more likely be nervous, anxious, depressed, and insecure in general, especially in the workplace. Conversely, the employees who have higher scores on the conscientiousness and extraversion scales tend to be responsible, organized, gregarious, and sociable, and it is more likely they will be satisfied with their work [3]. Hence, personality traits of neuroticism, extraversion, and conscientiousness displayed appreciable correlations with the employees’ job satisfaction [72].
\nBesides personal characteristics, situational characteristics also influence job satisfaction, which can explain what kinds of work tasks are especially satisfying. The situational factors include pay, opportunities for promotion, administration style, coworker, and working conditions [73]. For employees, a job is not “just a job.” Instead, it is a collection of tasks, relationships, and rewards. Any job-related conditions happened in the workplace may influence their emotion, which further impacts how they judge and perceive toward their job [3]. Therefore, in order for employees to have job satisfaction, the situational factors need to be carefully considered. For example, is the pay commensurate with the job duties? Is the pay secure? Are the promotions frequent, fair, and based on ability? Is the supervisor competent, polite, and a good communicator? Are the coworkers responsible, helpful, and interesting? Is the work challenging, interesting, respected? If it is yes to all the above questions, then it is highly possible that employees would be satisfied with their job [2].
\nThe needs of employees toward the work itself can be further realized through job characteristic theory. In other words, this theory helps to answer the question of how to design a task to make employees feel satisfied. Job characteristic theory suggested that job dimensions such as task identify, task significance, skill variety, autonomy, and feedback impact employees’ satisfaction with the work itself [3, 74]. Among these dimensions, skill variety, task identities, and task significance together produce a sense of meaningfulness of work, which reflects the extent the work tasks fit in the employees’ value and beliefs. The dimension of autonomy allows employees to experience the responsibility for outcomes of the work. Responsibility for outcomes refers to the extent the employees feel that they are responsible for the quality of the work. Providing either positive or negative feedback to employees make them have the opportunities to know the actual results of the work activities. Knowledge of results means that employees know how well or poorly they are doing. Thus, research suggests that the higher the three psychological states, the higher the working motivation, which leads to higher job satisfaction. An employee who has a high level of job satisfaction holds positive feelings toward his or her job, while he/she may hold negative feelings if he/she has a low level of job satisfaction [3].
\nThe next question to be answered is “does job satisfaction really matter?” This question can be answered through elaborating the relationship between job satisfaction and job performance, job commitment, organizational citizenship behavior (OCB), absenteeism, and turnover.
\nFirst, a number of researchers have been curious about the relationships between job satisfaction and job performance. For this question, many people may intuitively believe that job satisfaction is an important factor to impact job performance. Their presumption is that happy workers are more likely to be productive workers. However, at the early stage, the results indicated that job satisfaction was not meaningfully associated with job performance [75]. Till recently, studies showed that job satisfaction was moderately correlated with task performance. In other words, job satisfaction did predict job performance [2]. The satisfied employees who held positive feelings toward their work did a better job to fulfill the duties [76], to increase creativity in job [77], to enhance decision-making and problem-solving ability [78], and furthermore, to strengthen the memory and recall ability [79].
\nSecond, job satisfaction is interrelated to job commitment. Commitment is defined as that an employee identifies with a particular organization and its goals and wishes to remain as a member [3]. Commitment can be divided into three types, i.e., affective commitment, continuance commitment, and normative commitment, which are emotional-based, cost-based, and obligation-based, respectively [2]. Research found that job satisfaction was strongly correlated with affective and normative commitment but not correlated with continuance commitment [80]. Thus, the employees who have positively affective reaction to their jobs will be committed to their job and feel an obligation to remain in the organization [80–84].
\nThird, job satisfaction is moderately positive related to organizational citizenship behavior [2, 85]. OCB has been defined as “individual behavior that is discretionary, not directly or explicitly recognized by the formal reward system, and that in the aggregate promotes the effective functioning of the organization” ([86, 87], p. 4). Williams and Anderson found that the cognitive component of job satisfaction predicted the emergence of OCB [88], which was also supported by Moorman’s study [89]. Therefore, the satisfied employees would like to engage in more work-related behaviors to offer help to coworkers and increase desire to interact with others. OCB is extremely important for the employees to contact with the customers since it leads to improved customer evaluation of service quality [90].
\nFinally, job satisfaction reduces job turnover and absenteeism [91, 92]. Turnover refers to “…the voluntary and involuntary permanent withdrawal from an organization” ([93], p. 72). Since actual turnover behavior is difficult to measure, Lingard suggested using turnover intention as a predictor of actual turnover behavior [94]. Karatepe et al. found that job satisfaction was a negative association with turnover intention [95]. As to absenteeism, it refers to “unscheduled employee absences from the workplace” ([96], p. 144). Vroom found that low levels of job satisfaction contributed to higher absenteeism rates [97], and such a finding was confirmed by Clegg [98]. In addition, Drago and Wooden conducted a survey of 601 workers from Australia, New Zealand, Canada, and the USA and found that absenteeism was lower while employees’ job satisfaction was high [99]. The relationship between job satisfaction and turnover was stronger than between satisfaction and absenteeism [3].
\nThe concept of job training satisfaction was proposed by Schmidt [32]. He combined the definitions of job training and job satisfaction into one of the affective outcomes, called job training satisfaction (JTS). As mentioned above, training involves employees acquiring knowledge and learning skills that they will be able to apply on the job immediately [8]. Job satisfaction involves how an employee feels and what he/she thinks about the job [2]. Job training satisfaction, thus, is defined as “…how people feel about aspects of the job training they receive. Job training satisfaction is the extent to which people like or dislike the set of planned activities or dislike the set of planned activities organized to develop the knowledge, skills, and attitudes required to effectively a given tasks or job” ([32], p. 483). According to Schmidt, the definition of job training satisfaction has several key components [100]. First, the focus of evaluation is on-the-job training as a whole, rather than on a single part of training activities such as a training course, trainers, facilities, or training content. Second, it refers to a pleasurable or positive emotional state resulting from each element and the whole process before and after the job training, such as fulfillment of needs, enhancing motivation to learn, or satisfied with the transferring the learned competencies to the job. Third, the subjects of evaluation target on the trainees where formal or planned training activities are offered by the organization rather than the informal learning effort endeavors by the employees themselves. When measuring job training satisfaction, not only the employees’ feelings about the job training are measured but also the training activities offered by the organization are examined [32, 101].
\nIn the past, the impact of training on job satisfaction was not emphasized until it was found that job satisfaction tended to be higher where workplace training was held in organizations [102]. In order to explore the relationships between these two variables, Schmidt conducted a survey of job training and satisfaction for employees in customer and technical service department in nine major organizations in the USA and Canada to address how job training satisfaction impacts on job satisfaction [32]. According to his findings, job training satisfaction was not only highly correlated with job satisfaction but also significantly related to the time spent in training, training methodology, and content. However, it was not related to age, gender, and race/ethnicity. Extended researches have been carried out to explore the impact of job training satisfaction on other work attitudes. Huang and Su found that there is a negative relationship between job training satisfaction and turnover intentions [103]. It is stated that, when employees are satisfied with job training, they are more likely to stay in the organization and have lower turnover intentions. The research results have also indicated that the relationship between job training satisfaction and turnover intentions can be mediated by job satisfaction. Mansour et al. showed that there is a positive relation between job training satisfaction and normative commitment [100]. Moreover, job training satisfaction was found to be positively related to organizational citizenship behavior [104, 105], organizational commitment (OC), and job involvement (JI) [105]. The relationship between JTS and OCB can also be partially mediated by OC and JI [105]. From these research results, job training satisfaction is found to be able to enhance employees’ work attitudes such as job satisfaction, commitment, job involvement, and organizational citizenship behavior, which leads to the increase of job performance.
\nBased on the above discussion, a revised comprehensive model of training effectiveness is proposed and shown in Figure 3. According to Schmidt’s definition, job training satisfaction measures the employees’ feelings about the whole job training activities such as identifying the training needs, designing the training program, delivering training contents, activating learning occurring, and assessing training evaluation. Thus, different from the original model shown in Figure 2, the variable of job training satisfaction was inserted after the variable of training transfer to influence job satisfaction and job performance. That is, if the learners are able to perceive positively toward training program, to learn the job required knowledge, skill, abilities, and attitudes through training, and to succeed in transferring the learned competencies to real workplace, their satisfaction level toward training program must be high. For instance, on-the-job training, especially structured OJT, has been perceived as an effective training approach to achieve transfer of training owing to its occurrence at or near the workplace using actual facilities, enhancing skills acquisition, and removing learning anxieties [6, 33]. This allows the employees to be able to perform the job well and, in turn, feel satisfied with the training. Such high satisfaction toward job training leads to high level of job satisfaction and further results in high job performance but low turnover intention. These findings are interesting and valuable. Jones et al. ever mentioned that training can have an indirect effect on performance if it increases job satisfaction by making it easier for employees to perform the job or feel more valued [96]. From a series of studies, the impact of training on job satisfaction, job performance, and turnover intention has been confirmed. The variable of job training satisfaction can serve as a predictor to the employees’ job satisfaction, job performance, and turnover intentions.
\nThe revised comprehensive model of training effectiveness with insertion of job training satisfaction and job satisfaction.
The central thesis of this chapter is to present how job training plays a role in influencing the employees’ job training satisfaction, which then impacts job satisfaction and subsequently affects job performance and turnover intentions. Although training is a critical strategy to help organizations gain competitive advantages and its purpose is to help employees learn job-related competencies, job training satisfaction cannot be achieved without a well-prepared and designed training program. That is, at the beginning of the training program design, it is necessary to carry out a needs assessment to make the learning occur, which consists of organizational analysis, person analysis, and task analysis. While conducting training design and delivery during training, the learner-centered learning paradigm which has been emphasized recently may be considered as a preferred approach owing to its increasing learners’ learning motivation and learning engagement. After training, the training effectiveness is evaluated by assessing not only learning performance of knowledge, skills, and job-related behaviors but also affective outcomes such as self-efficacy, attitude, and motivation. Research has indicated that possessing a pleasurable or positive emotional state with the whole job training program, employees will have higher job satisfaction and job performance. Other job attitudes such as organizational citizenship behavior, affective commitment, and normative commitment will increase, while turnover intention and absenteeism will decrease. In this chapter, the comprehensive model of training effectiveness was modified by inserting the job training satisfaction after training transfer. This not only better elaborate the relationship among training, job satisfaction, and job performance but also serves as a reminder for the human resource practitioners who should always bear in mind how to make the trainees satisfied with the training when designing and delivering a training program.
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