741 publications from this institution
To address the issue of reducing emissions of greenhouse gases, organizations are involved with emergent markets for trading emission permits. Investment in equipment that reduces emissions may generate emission credits for sale in the market. This article applies real options analysis to actual case study information from British Petroleum-Amoco of a particular project that would generate emissions credits. We conclude that unless permits have a faster price rise than is generally anticipated, certain projects are not economically feasible. The policy implication is that planners may need to set more stringent regulations to bring about their desired result. Additionally, real options analysis in this market based regulatory policy is an especially important tool for the energy industry, which is disproportionately impacted by greenhouse gases policies.
Purpose Due to the different institutional pressure such as those from market, regulations and competitors, companies have implemented green supply chain management (GSCM). Unfortunately, tens of GSCM practices exist. Whether all companies should implement GSCM and how to achieve both environmental and economic performance are still not clear for many companies. The purpose of this paper is to develop models that can be helpful for companies to identify right GSCM practices and implement GSCM effectively and efficiently. Design/methodology/approach Based on about 18 years of study on GSCM with four surveys in China in 2001, 2005, 2012 and 2016, as well as numerous site visits and interviews mainly in China but also in Japan, Germany and Canada, this paper explores institutional drivers as well as opportunities and challenges using theoretical analysis and case studies. GSCM is defined considering a product life cycle. A key three-step GSCM approach is theoretically developed considering opportunities and challenges through life cycle analysis (LCA) of a product and position of a company. Findings All companies should implement GSCM practices to avoid risks. To effectively implement GSCM practices, a company should understand the life cycle of its product and its position in the supply chain. A key three-step LCA-based approach can help companies to identify the critical GSCM practices. Originality/value A key three-step LCA-based approach for GSCM implementation is originally developed based on theoretical analysis and eight years of study.
Purpose The purpose of this paper is to present the development of a methodology to evaluate suppliers using portfolio analysis based on the analytical network process (ANP) and environmental factors. Design/methodology/approach The authors develop a three‐step process, first by evaluating influence/power and performance scores of suppliers using ANP. They include environmental dimensions in this analysis, then map these suppliers onto a portfolio grid. Recommendations are also made on how to manage suppliers depending on what part of the portfolio they appear based on the scores. Findings The technique is useful and versatile. The paper clearly discerns various characteristics of the suppliers and produced recommendations on supplier management for an exemplary case scenario. Research limitations/implications The technique was applied for an illustrative example. Validation and application in a real world setting is required. There are many additional opportunities to further integrate other modeling tools into this process. Practical implications Managers can use this technique to help them more effectively deal with suppliers. The portfolio is a good tool for operational and strategic management of suppliers. Originality/value This tool is the first to apply ANP to supplier portfolio analysis. It is also the first tool to integrate and apply the portfolio supplier management approach to an environmentally oriented decision environment.
Greenhouse gas emissions are receiving greater scrutiny in many countries due to international forces to reduce anthropogenic global climate change. Industry and their supply chains represent a major source of these emissions. This paper presents a tactical supply chain planning model that integrates economic and carbon emission objectives under a carbon tax policy scheme. A modified Cross-Entropy solution method is adopted to solve the proposed nonlinear supply chain planning model. Numerical experiments are completed utilizing data from an actual organization in Australia where a carbon tax is in operation. The analyses of the numerical results provide important organizational and policy insights on (1) the financial and emissions reduction impacts of a carbon tax at the tactical planning level, (2) the use of cost/emission tradeoff analysis for making informed decisions on investments, (3) the way to price carbon for maximum environmental returns per dollar increase in supply chain cost.
Critical resources are key for low carbon development. International trade in critical resources is commonplace. It is important to clarify country roles within this trade network so that resource supply risk can be mitigated and low carbon industries can be supported. This study investigates global trade of typical ores and chemical compounds for lithium-ion batteries—lithium carbonate, cobalt oxide, nickel sulfate, manganese sulfate, nickel ore and manganese ore. The period 2010–2018 is selected to explore different country roles using network analysis. A competition trade model is developed to identify relationships between countries. A critical resource influence model is developed using bootstrap percolation theory to simulate impacts arising from dominant countries—those countries with rich resource endowments or mature markets. Results show that dominant countries tend to maintain close trade relationships. Trade scale is a key factor influencing each country's trade competitiveness and influence. Several policy recommendations are proposed to promote sustainable resource trade and use.
No abstract is provided for this article.
Blockchain technology use cases for supply chains—strategically and operationally—have been highlighted in practice and in research. In this respect, various applications of analytical models have been introduced to understand, analyze and make decisions related to blockchain phenomenon in production, operations, and supply chains. This work has received extensive—and some would argue unprecedentedly--rapid attention within the scholarly community. This early growth sets the stage for large-scale academic research and commercialization. Acknowledging this level of popularity, we provide a critical review of analytical models analyzing the current state-of-the-art research. This includes a synthesis of works that classify different research areas and general analytical model application within each research area. Bibliometric and network analysis tools help identify critical research contributions, key research areas, relationships among analytical models and research areas. Major findings include: (1) analytical models in this field are expanding rapidly; (2) the International Journal of Production Economics has been central to the analytical and production economic modeling research discourse; (3) ten research areas including antecedents, actions, scenarios and consequences are identified from a network analysis; and (4) the relationship between analytical models and research areas is evolving with insight into why and in which direction this work is likely to continue. We identify significant research gaps with great potential for scholarly advancement.
In order to advance scientific knowledge, it is important to maintain consistency regarding the methodologies and units/levels of analysis employed to test a theory's main claims. Thus, this investigation provides a critical examination of the papers that have aimed to test the trade-off model and its competing concepts. The analysis focuses on the methodologies used to examine the validity of such models and theories, and also on the operationalisation of the variables that represent the level of analysis by which those theories are tested. To aid in the investigation, a framework to distinguish measures of performance with an internal and external reference and perspective is proposed. The results show that current methodologies, approaches and rationales used to determine the validity of the trade-off model or its rival concepts observe important limitations, as they do not address the trade-off model's core principles. Those limitations in turn make the results of those studies questionable. Consequently, it is proposed that in order to advance theory in our field, more consistent methods and approaches should be utilised.
No abstract is provided for this article.
Over the past two decades, we have seen a growth in enterprise resource planning (ERP) systems adoption by organisations. Even with the many benefits offered by such systems, there have also been many failures. One of the important reasons for these failures is inappropriate project evaluation and selection. In order to reduce the level of project failures, we introduce an innovative methodology, the Financial Appraisal Profile (FAP) model, which seeks to address some of the issues and limitations posed by standard appraisal and evaluation approaches for strategic technologies and programs. By making the right decision in the first place and involving senior managers in the appraisal process, the organisation will be better placed to achieve project success. The adoption of a management team approach to investment appraisals will not only enhance the information base, but will also result in greater managerial commitment to a project. We believe by adopting the FAP model, greater awareness to strategic issues and goals will also be achieved, which should lead to a more focused top management team — with all members pulling in the same direction.
Research on internal auditor selection has had limited exposure in the auditing literature. Recently Seol & Sarkis introduced a multi‐attribute decision model, an analytic hierarchy process (AHP), for the process of internal auditor selection. The purpose of this paper is to extend and validate the proposed model by Seol & Sarkis in an actual internal auditor selection process. Real case information from a trading company in Hong Kong that has gone through a recent experience in hiring entry level internal auditors was used for the study. Data were collected using an intensive survey of the importance of each attribute/skill provided by the Competency Framework for Internal Auditing (CFIA) and followed by an actual application of such skills in a recent hiring experience. Results show the effectiveness of AHP and the comprehensive characteristics of the factors involved in the decision. Further implications of the method are also discussed in the paper.
Empirical research in the area of corporate sustainability highlights potential conflicts between corporate financial performance and environmental performance. In such a situation, agency theory arguments applied to the corporate environmental context predict that top management compensation should be explicitly linked to environmental performance in order to bring about proper alignment of organizational environmental goals and management incentives. We test this proposition for a sample of 207 Standard & Poor 500 firms in the US in 1996 who explicitly report in Investor Responsibility Research Council (IRRC) surveys the presence or absence of a contractual link between environmental performance and executive compensation. We find that only in firms with an explicit linkage between environmental performance and executive contracts is there is any evidence of a significant impact of firm‐level environmental performance on CEO compensation levels. However, even this impact is not very impressive since (a) it holds only for IRRC compliance and spill indices and does not hold for IRRC toxic emission indices, and (b) even the effects for compliance and spill indices do not hold relative to industry levels of these indices. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.
Research joint ventures (RJVs) are project environments that typically focus on the development of innovations and ideas. The development and management of knowledge is the primary objective for these RJVs. To help understand the practices and characteristics of RJV knowledge management and learning processes we introduce a taxonomy for these types of project environments. Using existing literature and supporting case study examples, a four-cell grid is developed to categorize RJVs. The grid is based on two dimensions, namely, the locus of the RJV research, which is concerned with the ‘newness’ of the knowledge, and the knowledge management approach, which is concerned with the learning and knowledge integration processes.
Sustainable supply chain management (SSCM) faces greater complexity because it considers additional stakeholder requirements, broader sustainable performance objectives, increased sustainable business practices and technologies, and relationships among those entities. These additional complexities make SSCM more difficult to manage and operate than traditional supply chains. Complex systems require new methods for research especially given reductionist research paradigms of modern science. Rough set theory (RST) can be a valuable tool that will help address complexity in SSCM research and practice. To exemplify RST usefulness and applicability, an illustrative application using sustainable supply chain practices (SSCP), and environmental and economic performance outcomes is introduced. The conceptual case provides nuanced insights for researchers and practitioners in mitigating and evaluating various SSCM complexities. RST limitations and extensions are introduced.
Reverse logistics has emerged as an important dimension for organizations to build their strategic advantage. Part of this effort relies on potentially out
The mining and extractive industry’s operations have significant harmful environmental consequences. Mining companies have started adopting green supply chain management (GSCM) practices which include green information technology systems (GITS) to help provide economic benefits while seeking minimal environmental damage. These mining organizations face significant hurdles related to introducing and implementing various GSCM practices which can address some of the environmental burdens. This study addresses this issue by adopting a GSCM practices framework and applying a novel decision support method that integrates grey numbers with DEMATEL and the NK model for evaluating and developing an implementation path model. Using a multiple case field study with input from managers of the Ghanaian gold mining industry, the adopted GSCM practices framework and methodology is applied. The results provide an evaluation and development path model to guide these organizations and managers for GSCM planning and investment decisions. The path results show that these organizations should first develop SSP (Strategic Supplier Partnership) with their suppliers for implementing GITS (Green Information Technology and Systems) and other GSCM practices. These results provide some exploratory insight and guidelines for managers and policy-makers who seek to integrate green initiatives. This study also sets the stage for further investigation of organizational greening in developing countries and the mining industry.
No abstract is provided for this article.
Supplier selection is one of the most important activities of organisations, where the short- and long term success of a buyer's organisation depends upon proper selection of its suppliers. The current competitive environment has placed increasing competitive pressures on suppliers to match the needs of buyer(s) in terms of quantity, quality, product mix, cost, time and place of delivery, to name a few performance measures. The focus on competitive supply chains and extended enterprises requires the adoption of agile manufacturing practices requiring their suppliers to have agile attributes. This study designs and implements a procedure for judging the suitability of suppliers for an organisation competing on agile manufacturing characteristics. Quantitative and qualitative factors are used to appraise and select appropriate suppliers to fit within an organisation's agility practices. In seeking to achieve this task, the synergistic integration of two techniques, the Analytical Network Process (ANP) and Data Envelopment Analysis (DEA) is applied in a multi-phased supplier selection approach. Initially, ANP is executed to appraise suppliers on their qualitative benefits, generating quantitative data from these qualitative dimensions. Secondly, DEA is used to synthesise the data to arrive at a ranking of the suppliers. The technique is validated in a small company case study.
Enterprise information technologies (EITs), which are strategic systems seeking to integrate the processes and databases of the entire organization and beyond, require a significant investment of money and human resources in return for the promise of a global business model and its associated far-reaching benefits. Their evaluation/justification must be completed with organizational goals and requirements included in the decision, or the organization could lose financially and competitively. Besides traditional financial models, e.g., ROI (return on investment), that are primarily meant for short-term financial justification purposes, there is a paucity of methods for the evaluation of the strategic and intangible costs and benefits that EITs afford organizations as a whole. This article introduces the use of a robust quantitative technique called the analytical hierarchy process (AHP) that can integrate a diverse range of factors (strategic and operational, and tangible and intangible) into one model. the approach can be easily understood by managers and analysts and has a history of application to other types of strategic justification decisions.
