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The purpose of this paper is to present how complexity on retail supply chains should be recognized and its relationship with the performance. Different supply chain structures and planning horizons have been analyzed to support practitioners taking action on the short, mid and long terms. Confronted complexity in the supply chain has been categorized as system, perceived and value adding. This would also help practitioners to understand the sources of the complexity and if the complexity is useful for the system or not.

Three different retail supply chain scenarios – each concentrating on different planning horizons – have been simulated on system dynamics software STELLA. Using the new classification scheme for complexity and suggested performance metrics, a multi-perspective analysis has been performed on the STELLA output.

The results and the methodology can be easily applicable in practice to support decision-making process and to answer “what-if” type scenario analysis on systems design and configuration. Using the selected complexity metrics, complexity of the system considering time factor – static and dynamic – and different information levels – system, perceived and value adding – has been evaluated. Used complexity metrics indicate the problematic areas in the systems to be distinguished.

This paper uses system dynamics modeling in retail supply chains to derive insight about dynamic behavior and to represent the complex interactions and a new classification scheme for system complexity.

This study aims to explore the phenomenon of training engagement from the trainers’ perspective. Specifically, two questions guided this inquiry. First, how do trainers define engagement in the training context? and What strategies do trainers use to engage trainees?

The collective case study approach was adopted for this qualitative study. Seven cases were selected for in-depth analyses. Data were collected through individual, face-to-face interviews and analyzed using the constant comparative analysis method.

Major findings suggest that engaging training practices take various forms. They include being trainee-centered, maximizing learning through entertaining and interesting instruction, accommodating different learning styles, eliciting trainee participation by creating an encouraging learning environment and connecting with trainees by building rapport early in a training session.

The small sample limits the generalizability of the findings. However, this study expands training literature by focusing on an under-explored research area, the role of engaging trainees in maximizing learning outcomes.

For trainers, this study offered some specific strategies they can use to engage learners in the training context to achieve desired learning outcomes. In addition, the seven cases selected for this study may be used as a benchmark against which both experienced and novice trainers compared their own practices.

This is one of very few qualitative studies with a focus on emotional aspects involved in training. The rich data from this study shed light on areas for future improvement, particularly regarding how to effectively engage trainees to maximize learning outcomes.

This teleobservation pilot study focuses on an innovative approach for the preparation of elementary social studies preservice teacher candidates through the use of interactive videoconferencing to provide observations of elementary classrooms. Preservice teacher candidates observed social studies lessons team-taught by regular classroom teachers and university professors in public school classrooms via videoconferencing equipment. Preservice teacher candidates remained on campus while another professor guided them through the social studies observation. Qualitative data were collected from preservice teacher candidates completing their social studies methods course through reflective summaries, KWL charts, and archived threaded discussions. The benefits and challenges of teleobservation are discussed along with implications and possibilities for future work. Specifically, the goals of this project included providing future social studies teachers with the following opportunities: 1) observe an elementary classroom in real-time; 2) discuss teaching as it is happening, and 3) observe university social studies professors modeling theory into practice.

The traveling purchaser problem (TPP) has gained attention in academics to deal with different variants in real business world. This study aims to study a green TPP with quantity discounts and soft time windows (TPPQS), in which a firm needs to purchase products from a set of available markets and deliver the products to a set of customers.

Vehicles are available to visit the markets, which offer products at different prices and with different quantity discount schemes. Soft time windows are present for the markets and the customers, and earliness cost and tardiness may incur if a vehicle cannot arrive a market or a customer within the designated time interval. The environmental impact of transportation activities is considered. The objective of this research is to minimize the total cost, including vehicle-assigning cost, vehicle-traveling cost, purchasing cost, emission cost, earliness cost and tardiness cost, while meeting the total demand of the customers and satisfying all the constraints. A mixed integer programming (MIP) model and a genetic algorithm (GA) approach are proposed to solve the TPPQS.

The results show that both the MIP and the GA can obtain optimal solutions for small-scale cases, and the GA can generate near-optimal solutions for large-scale cases within a short computational time.

The proposed models can help firms increase the performance of customer satisfaction and provide valuable supply chain management references in the service industry.

The proposed models for TPPQS are novel and can facilitate firms to design their green traveling purchasing plans more effectively in today’s environmental conscious and competitive market.

The organizational learning and learning organization literatures lack empirical support in delineating the role leaders play in fostering or hindering learning. This study aims to build upon previous research on facilitative leadership in learning organizations to consider how leaders contribute to and detract from learning at the individual and organizational levels in the corporate context.

Preliminary survey research confirmed that the Fortune 500 company being considered for the study was perceived as a learning organization by its employees. The study then proceeded with critical incident interviews with managers and their direct reports, resulting in a cross‐case content analysis of four categories: triggers, beliefs, behaviors, and outcomes, which prompted the development of a preliminary model of the learning process depicted by participants.

The findings revealed that learning leaders have several distinct characteristics and skills, but the participants gave the most emphasis to emotionally intelligent communication, a prominent feature of facilitative leadership.

The study represents the perceptions of participants within a particular context at a specific time. Future research could include longitudinal, cross‐cultural studies that focus on communication processes related to learning.

The study confirmed the importance of facilitative leadership while highlighting both cognitive and emotional aspects of learning. It also pinpointed mechanisms for institutionalizing learning.

The study offers empirical support for the centrality of facilitative leadership while pinpointing communication competence and emotional intelligence as essential aspects of effective learning leadership.

The purpose of this paper is to provide a context for the compilation of papers and commentaries included in this International Journal of Organizational Analysis special issue on “Scripting the next wave of exigent issues for service‐learning in our unscripted future: when technology, globalism, and community engagement collide.”

The authors of this paper are the Guest Editors for the special issue. As such, in this paper, they provide a brief history of why the special issue was created and how it serves as an extension to the first special issue (Vol. 17 No. 1, 2009).

There are five papers and six commentary pieces included in this special issue. Each raises a charge, or challenge, to the reader in terms of moving forward with service‐learning in the uncertain, complex, and highly unscripted environments.

The practical implications of this paper are those that relate to future research and practice in the service‐learning domain. This is contextualized as part of the collective challenge as the author move forward in a world where local, regional, national, and international connectedness intersects with social, economic, and technological pressures.

As the introduction, this paper is unique in that it provides an overview of the contents for the entire special issue.

Explains why, following China‘s implementation of a market economy, public accounting firms were required to affiliate (hook‐up) with existing government or educational institutions until 1993 when partnerships and limited liability firms were also allowed. Describes the rules relating to independent accounting firms and changes which should foster their development but reports that, in fact, most firms are still affiliated. Discusses the reasons for this and the resulting problems, e.g. lack of competition and independence, low quality of service and increases in fraud, misrepresentation and under‐disclosure. Reveals that despite the 1995 exposure draft on eliminating the hooking‐up structure few de‐affiliations have taken place and identifies four problems which need solving if full de‐affiliation is to be achieved.

This paper seeks to construct a model for inventory management for multiple periods. The model considers not only the usual parameters, but also price quantity discount, storage and batch size constraints.

Mixed 0‐1 integer programming is applied to solve the multi‐period inventory problem and to determine an appropriate inventory level for each period. The total cost of materials in the system is minimized and the optimal purchase amount in each period is determined.

The proposed model is applied in colour filter inventory management in thin film transistor‐liquid crystal display (TFT‐LCD) manufacturing because colour filter replenishment has the characteristics of price quantity discount, large product size, batch‐sized purchase and forbidden shortage in the plant. Sensitivity analysis of major parameters of the model is also performed to depict the effects of these parameters on the solutions.

The proposed model can be tailored and applied to other inventory management problems.

Although many mathematical models are available for inventory management, this study considers some special characteristics that might be present in real practice. TFT‐LCD manufacturing is one of the most prosperous industries in Taiwan, and colour‐filter inventory management is essential for TFT‐LCD manufacturers for achieving competitive edge. The proposed model in this study can be applied to fulfil the goal.

Owing to keen challenges in an evolving market, new product development (NPD) is critical for an enterprise to prosper. To increase the likelihood of having a few successful products, NPD mix is usually selected in practice. Since, a firm has difficulty surviving independently in a high technology industry, flexible strategies to collaborate or to compete with firms within a technology innovation network (TIN) are essential. Therefore, finding an appropriate mix which can lead to a more satisfactory performance for an enterprise inside a TIN is an important issue, which this paper aims to discuss.

A modified‐analytic hierarchy process (AHP) model is proposed to evaluate the NPD mixes. Since, integrated product development is positively associated with efficiency and negatively with innovation, a suitable NPD operation with a mode of knowledge creation needs to be adopted by evaluating the result of the NPD mix.

The proposed model leads to a more satisfactory performance for the firm.

The result from the practical case study is in accord with the theoretical model, since this model keeps a firm operating simultaneously efficiently and innovatively, rather than trade‐off and balanced.

Most industries have become increasingly competitive nowadays, and a good supply chain relationship is essential for a company to survive and to acquire reasonable profit. Therefore, supplier selection is very important. The purpose of this paper is to propose a novel model for evaluating the performance of suppliers.

A supplier performance evaluation model based on analytic hierarchy process (AHP) and data envelopment analysis (DEA) is constructed. DEA is applied first to evaluate quantitative factors, and the results are transformed into pairwise comparison values for AHP analysis. Qualitative factors are also evaluated through AHP analysis, and a final ranking of suppliers can be obtained by combining the quantitative and qualitative results.

The proposed model can be applied to evaluate and select the most appropriate integrated circuit packaging company for outsourcing. With the incorporation of experts' opinions and the consideration of qualitative and quantitative factors, the model can provide a both subjective and objective supplier performance ranking.

The proposed model can be tailored and applied to supplier evaluation and selection in other industries.

Although many models are available for supplier evaluation, this paper considers both the subjective and objective performance characteristics simultaneously in the evaluation process.