Risk matrix driven supply chain risk management: Adapting risk matrix based tools to modelling interdependent risks and risk appetite

There is a major research gap of developing a supply chain risk management process integrating the risk appetite of a decision maker and all stages of the risk management process within an interdependent network of systemic risks. We introduce an iterative process, namely risk matrix driven supply chain risk management, to bridge this gap. We make use of the recently introduced concept of utility indifference curves based risk matrix to capture the risk attitude of a decision maker. We also present algorithms for assessing and mitigating interdependent risks for risk-neutral and risk-averse/seeking decision makers and demonstrate the application of our proposed process through a simulation study. Utilising the method of cost-benefit analysis within an interdependent setting of interacting risks and risk mitigation strategies, we also propose a second approach that can help a decision maker to determine a set of Pareto-optimal risk mitigation strategies and select optimal solutions subject to the budget constraint and specific risk appetite

The long-run relationships between transport energy consumption, transport infrastructure, and economic growth in MENA countries

This paper investigates the impact of transport energy consumption and transport infrastructure on economic growth by utilizing panel data on MENA countries (the Middle East and North Africa region) for the period of 2000-2016. The MENA region panel is divided into three sub-groups of countries: GCC panel (containing the Gulf Cooperation Council countries), N-GCC panel (containing countries that are not members of the Gulf Cooperation Council), and North African countries (called MATE — Morocco, Algeria, Tunisia and Egypt). Using the Generalized Method of Moments (GMM), we find that transport energy consumption significantly adds to economic growth in MENA, N-GCC and MATE regions. Transport infrastructure positively contribute to economic growth in all regions. The Dumitrescu-Hurlin panel causality analysis shows the feedback effect of transport energy consumption and transport infrastructure with economic growth. The empirical results add a new dimension to the importance of investing in modern infrastructure that facilitates the use of more energy-efficient modes and alternative technologies that positively affect the economy with minimizing negative externalities

Dealing with endogeneity bias: The generalized method of moments (GMM) for panel data

Endogeneity bias can lead to inconsistent estimates and incorrect inferences, which may provide misleading conclusions and inappropriate theoretical interpretations. Sometimes, such bias can even lead to coefficients having the wrong sign. Although this is a long-standing issue, it is now emerging in marketing and management science, with high-ranked journals increasingly exploring the issue. In this paper, we methodologically demonstrate how to detect and deal with endogeneity issues in panel data. For illustration purposes, we used a dataset consisting of observations over a 15-year period (i.e., 2002 to 2016) from 101 UK listed companies and examined the direct effect of R&D expenditures, corporate governance, and firms’ characteristics on performance. Due to endogeneity bias, the result of our analyses indicates significant differences in findings reported under the ordinary least square (OLS) approach, fixed effects and the generalized method of moments (GMM) estimations. We also provide generic STATA commands that can be utilized by marketing researchers in implementing a GMM model that better controls for the three sources of endogeneity, namely, unobserved heterogeneity, simultaneity and dynamic endogeneity

Nature of technology and location effects on firm performance in the US medical device industry

This paper examines the location effects on firm performance (sales, employment and market value) by analyzing geographical and technological proximities in the US medical device industry. The nature of technology is introduced as a new way to scrutinize the impact of various proximities, and the findings indicate that the geographical and technological proximity in itself does not affect performance, whereas the spatially-mediated technological proximity, characterized by the technological proximity within a cluster, positively influences the performance of medical device firms. The paper addresses an important theoretical question. It consequently contributes to the effects of different proximities and nature of technology on firm performance and provides relative managerial implications interlocked with insights obtained from the medical industry

Symbolism in Khalida Hussain's Short Stories

Khalida Hussain is an eminent Urdu short story writer. She is an introvert in her short stories. Her short stories comprise multi-dimensional meanings. To attain this purpose, she writes in symbolic style mostly. This article attempts to analyze her short stories from the perspective of symbolism. Sometimes she uses concrete symbols and sometimes an abstract way of writing. Her symbols are neither so easy, nor so difficult to understand.  She chooses them from life, society, folklore, literary traditions, eastern culture, and myth. She uses these symbols to express her inner feelings, self-actualization, stream of consciousness, interior monologue, existentialism, psychological problems, and also matters related to society. These symbols vary from each other and demand deep intention to understand them

Barriers to Information and Digital Technologies Adoption in Humanitarian Supply Chain Management : A Fuzzy AHP Approach

Peer reviewedPostprin

Towards customization : Evaluation of integrated sales, product, and production configuration

Acknowledgement We are grateful to the anonymous reviewers for their constructive comments, which helped us improve both the quality and presentation of the paper.Peer reviewedPostprin

Analysing corporate governance and accountability practices from an African neo-patrimonialism perspective : Insights from Kenya

The authors thank the Editors of this Special Issue, including the Managing Guest Editor Dr Philippe Lassou, and the two anonymous reviewers for their insightful feedback and comments that greatly improved our manuscript. The authors are also immensely grateful to Professor Teerooven Soobaroyen for his useful suggestions and critique of earlier versions of this paper, and whose feedback has helped to improve its quality significantly. Finally, we acknowledge the input of delegates at the 9th Asia-Pacific Interdisciplinary Research in Accounting (APIRA) Conference, held in Auckland, New Zealand.Peer reviewedPostprin

Measuring agri-food supply chain performance and risk through a new analytical framework: a case study of New Zealand dairy

Many researchers and practitioners have long recognized the significance of measuring performance. Although general guidelines for measuring business performance are widely available, no appropriate measurement frameworks have been developed for measuring agri-food supply chain performance. Particularly, food quality and risk-related indicators have not been well integrated into existing performance measurement systems. Our research, therefore, addresses this knowledge gap by first providing an in-depth review of extant performance measurement systems and frameworks. It then develops an analytical framework by extending the Supply Chain Operations Reference (SCOR) model which has been extensively implemented across non-food industries. The analytical framework is further validated by utilizing a case study of 50 farmers and 10 dairy companies, operating in the New Zealand dairy industry. Our pilot testing and subsequent findings show that the individual metrics interlocked with the analytical framework are in-line with the key industrial practices adapted by the New Zealand dairy industry. In addition, the framework is flexible and scalable to evaluate and benchmark other agri-food supply chains–ranging from fresh products such as fruits and vegetables to processed foods such as canned fruits. The findings further show that the detailed information required for measuring the level-3 SCOR metrics is not easily available in the industry, as researchers need to access specific company records that may be confidential. Consequently, this study provides how agri-food supply chain managers can employ our new analytical framework in-conjunction with the SCOR model for a deeper understanding of the complicated performance measurement indicators applied in their agri-food production systems and relevant supply chains