ارزیابی برنامه های توسعه تامین کننده سبز در ارائه دهنده سیستم های ارتباط از راه دور

Green supplier development has become necessary as organizations increasingly compete on environmental supply chain capabilities. However, formal modeling tools to aid managers in evaluating green supplier development programs (GSDPs) are virtually non-existent. This paper introduces a formal structured managerial approach for organizations to help evaluate the influence relationships amongst GSDPs. Utilizing GSDP categorizations we acquire multi-functional managerial inputs within a telecommunication systems provider to evaluate the GSDPs. The managerial inputs are evaluated using a formalized grey-based DEMATEL methodology. Managerial and research implications of the proposed study and application, limitations and future research directions are also detailed.

The green supply management literature has focused on aiding existing suppliers improve their environmental performance by ‘requiring’ these suppliers to acquire certifications or introduce green practices. Alternatively, some companies green their supply chains through selection of existing green suppliers. Not all suppliers are in the position to effectively, on their own, improve their environmental or sustainability performance. Also not all suppliers are initially green. Similar to organizations aiding their suppliers to improve upon business and competitive performance, such as costs, quality and delivery, organizations may also aid their suppliers' green development. A critical aspect of green supply chain management literature that has been under-researched has been this issue of supplier development (Seuring and Müller, 2008a). Interestingly, even though significant research has been initiated and completed on green supply chain management (Srivastava, 2007, Seuring and Müller, 2008b, Ilgin and Gupta, 2010 and Sarkis et al., 2011), investigation into green supplier development programs (GSDPs) is virtually non-existent. The development or application of formal tools and models has been very limited in general supplier development programs (Bai and Sarkis, 2010a). Some formal models that have been developed consider the further development of suppliers through, for example, adjusting supplier practices in response to requests for proposals (Narasimhan et al., 2008b). Formal decision and management models are recommended by the literature to help in supplier improvement and management (Krause et al., 1998 and McGovern and Hicks, 2006). Formal tools and models for environmental supplier development to aid companies manage environmental performance of suppliers are even more limited. Formal modeling tools for organizations to green their supply chains need to help them determine how they should develop and implement their GSDPs. That is, some GSDPs will be more valuable or foundational (influencing development of other supplier development programs). In recognition of this fact, we introduce a formal methodology to investigate the importance of organizational GSDPs and how they relate to each other. To help develop these relationships we introduce a novel grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach to structure the program management environment. One important purpose of this formal modeling approach is to aid organizations prioritize their investments in GSDPs while also identifying critical relationships amongst them. Prioritization and relationship identification of GSDPs potentially helps organizations to free up resources and enhance their organizational returns by focusing on the most important programs that set the foundation and relationships to other environmental programs and goals. This formal modeling methodology is valuable for planning, design, implementation or maintenance of GSDPs in organizations. The formal modeling approach introduced in this paper, using a grey-based DEMATEL approach, incorporates a number of stages resulting in a relationship diagram amongst various GSDPs on prominence and cause/effect axes, a prominence–casual relationship diagram. The technique involves the identification of GSDPs, understanding their interrelationship utilizing “grey” data input from management, transforming the grey data into crisp data, completing a series of DEMATEL steps, and eventually arriving at a final prominence–causal relationship diagram with associated analysis. The goal of this paper is to introduce and explicate how grey-based DEMATEL can be a valuable managerial tool to evaluate GSDPs and their relationships to each other and importance for the organization. The paper begins with a short discussion and review of GSDPs and some previous work on evaluating the relationships of these programs. In addition, some background on related tools for analysis of GSDPs that do exist will help us identify what gaps occur in the literature. We then generally introduce the basic concepts associated with grey-based DEMATEL. In the following section we apply the technique to a real-world situation that provides managerial insights and implications for the methodology and its results. The results are presented with some discussion analyzing the results and implications of the technique with feedback from management. We finally conclude the paper with some limitations and future research directions in this emergent field and topic.

In this paper we introduced and described how grey-based DEMATEL can be a valuable managerial tool to evaluate GSDPs. The study specific focus was on GSDP relationships to each other as well as importance of GSDPs tor the organization. We introduced a practical application/case study of this technique in a telecommunications provider organization. The analysis for this organization showed that even though a number of GSDPs were implemented, their focus was relatively adversarial and less collaborative with its suppliers. A sensitivity analysis showed that this finding may not be the case for all functions and managers that deal with suppliers. The managerial implications and usefulness of the technique are clear. Managers are able to determine what GSDPs within their organization need more attention and which GSDPs may be given less priority. Managers also complete sensitivity analyses in ways that allow them to determine the stability of their observations. Over time, they may also use the technique to help plan the direction of their organization by determining how particular GSDPs influence each other. For example, if they wish to further develop existing GSDPs or other programs the digraphs provide clear relationships on which GSDPs should be emphasized, and resourced, to insure greater success of programs. Researchers can also find this tool valuable for either broad based or single in-depth case studies. For example, comparative analyses across case study organizations may help identify particular characteristic of the relationships of GSDPs. The prominence–causal diagrams may be used to identify the various structures and relationships of different companies whether based on size, industry, product family or other characteristics typically used for comparative analyses of cases. Longitudinally, the results may also change depending on the strategic emphasis of the organization and these observations may be completed over time with the same case company. Even with managerial and research insights provided by this methodology, there are still limitations. These limitations set the stage for future research. One major limitation is the evaluation effort required with this technique. For this study evaluators each had to complete over 272 pairwise comparisons. Fatigue is certainly a possibility which may cause some reliability problems. One way to overcome this difficulty is to group the factors and complete a hierarchical evaluation of the relationships. Another limitation is the evaluation of the ‘importance’ of the factors in these types of studies which is based on the level of influence (connectedness) of factors on each other. Influence may not necessarily be a good importance value for factor. For example, even a program that does not have a strong causal relationship to other programs may be critical to the company due to strategic issues facing the organization. This information is not necessarily captured by the methodology. Incorporation and inclusion of other ranking approaches (e.g. the analytical hierarchy process or rough set theory) may provide ways of overcoming this limitation. An additional limitation is our utilization of a given grey-scale value for a linguistic variable. These values were assumed. Careful consideration and investigation of grey scale/linguistic assignments and dispersion of the grey scale could be investigated to determine the sensitivity of the solution. These general limitations represent future directions for research. In addition, future research into a comparative analysis of this across multiple companies may be of interest to determine the generalizability of GSDP relationships. The application to other, general, supply chain and environmental sustainability issues may also be an interesting research stream. Overall, this approach is flexible and useful for application in a broad variety of managerial and decision environments. We believe this research sets the stage for significant future investigation in sustainable supply chain management research.