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Organisational planning identifies two areas — corporate culture and human resources — which have received much attention as key areas in formulating strategic plans in many organisations. Traditional planning fails to give flexibility in the face of foreign competition, technological advancement, etc., and therefore management must adjust their managerial style to accommodate new performance criteria, reward systems and other innovative ideas, to progress successfully.

Logistics practitioners must continually improve inventory management processes as they daily respond to the twin drivers of customer satisfaction and cost efficiency. The purpose of this paper is to investigate the scenario of sourcing goods through lateral transshipments in a periodic-review policy setting, against a backdrop of cost optimization objectives.

The authors develop decision rules that make cost-optimized selection between backordering and combined reactive and proactive lateral transshipment options possible. This necessarily takes account of the trade-off between purchasing, holding and backorder cost components. In addition, the authors use simulation studies to illustrate the superior performance of the proposed decision options.

According to results of the simulation studies, the proposed two-step decision rule generates the lower inventory cost than the alternative decisions rules. The outperformance of proposed two-step decision rule is valid in different scenario.

This study develops the decision rules to assist wholesaler logistics practitioners to make optimized decisions with regard to whether they should proactively lateral transshipments and if selected, the optimum size of the extra lateral transshipment.

This study has made a significant contribution to the existing knowledge base as it develops decision rules for a combined proactive and reactive approach using lateral transhipments to meet both urgent demand and a part of the demand expected during the supplier lead time in a cost-efficient way.

The purpose of this paper is to propose a three-tier assessment model (TAM), aiming to identify and evaluate the competitiveness level of companies. The existing problem is that companies find it difficult to choose a proper model which can be deployed to benchmark with competitors in terms of their competiveness level in the marketplace. Most of the available models are not appropriate or easy to use. The proposed assessment model is able to provide an insight for better planning and preparation so as to gain a better chance of success comparing with their competitors. Most importantly, the proposal model adopts a pragmatic approach and can be implemented without going through tedious mathematical calculations and analysis.

TAM embraces three different approaches deployed in various stages of the application process. The first stage is to identify the relevant criteria using hierarchical holographic modeling and the second stage is to assess the associated weightings of these criteria used to rate the potential competitiveness of related companies. The technique used in stage two is known as fuzzy analytic hierarchy process (FAHP) which is a combination of two well-established methods including fuzzy logic and analytical hierarchical programming. In stage three, a technique known as technique for order preference by similarity to the ideal solution (TOPSIS) is adopted to benchmark the level of competitiveness covering several companies in the same industry.

In this paper, a case study is conducted in order to validate the feasibility and practicality of the proposed model. Results indicate that TAM can be easily applied in various industrial settings by practitioners in the field for supporting operations management practices.

Significant amount of work is needed to ensure that the proposed model can be practically deployed in real industrial settings.

This proposed model is able to capitalize on the benefits of the HMM, FAHP and TOPSIS methods and offset their deficiencies. Most importantly, it can be applied to various industries without complex modification.

This paper suggests a hybrid model to assess competitiveness level embracing three different techniques with the unique feature which is able to provide an insight for better planning and preparation in order to excel competitors. Companies may be able to follow the procedures and steps suggested in the paper to implement the model which is proven to be pragmatic and can be applied in real situations.

Frequent food safety incidents caused widespread consumer concerns. Even though food safety is one of the weakest links in the fresh food supply chain and influences consumer food choice in ways different from the quality dimension, this factor is hardly proposed as one of the key traditional supplier selection criteria (e.g. quality, delivery, and price) in the literature. The purpose of this paper is to develop a business process decision model to assess the non-compensating food safety sub-criteria in order to disqualify fresh food suppliers that cannot reach the minimum threshold for low probable food safety failure. The preferred fresh food suppliers can minimize the risk of food safety failure and the associated huge food safety failure costs spanning from private consumer anguish to social distress that cause unbearable costs of sales loss and damage to brand image in business.

This study proposes a novel approach that combines several well-established multi-criteria decision making (MCDM) techniques, including fuzzy AHP (FAHP), TOPSIS, and ELECTRE, and innovatively apply to analyze supplier performance and prioritize potential fresh food suppliers. This hybrid business process model can enforce compliance to all the five non-compensatory sub-criteria of food safety. Since ELECTRE is a non-compensatory MCDM method, it is therefore particularly applicable for disqualifying high risk fresh food suppliers from further full scale supplier performance evaluation by FAHP and TOPSIS. This hybrid business process decision model is able to capitalize on the strengths of these MCDM methods and offset their deficiencies.

This study uses data of an international supermarket chain to validate feasibility of the proposed model. Results indicate that this model is able to assess the non-compensating food safety sub-criteria via the ELECTRE method in order to disqualify fresh food suppliers that cannot reach the minimum threshold for low probable food safety failure. Only the preferred suppliers with the required food safety capability can proceed to the second stage of the supplier selection process. Assessment via the TOPSIS method reveals the ranking order of those top performing suppliers according to their relative scores along all the supplier selection criteria. The TOPSIS ranking results with the selection of the suppliers C, E, A, and F are robust and consistent across all the different scenarios.

Application to the fresh food industry is possible with the aid of the MCDM methods. The contribution to the body of knowledge in this teaching and research field demonstrates the importance of first identifying the order qualifier for disqualifying those suppliers that do not satisfy the food safety requirements via the ELECTRE method. The proposed assessment procedure complies with the regulatory policy on food safety, and would influence public policy in applying the best practice of food safety regulation. Without first qualifying the potential suppliers on the basis of food safety, wrong decision can be made to select those high food risk suppliers that have relatively higher overall scores in other supplier selection criteria. Using the assessment results has positive economic and commercial impact on the purchasing managers to formulate appropriate purchasing and supplier development strategy to enhance supplier’s food safety performance, whilst maximizing the overall supplier portfolio performance. The improved supplier’s food safety performance will certainly benefit the society’s quality of life as well.

Based on the analytical MCDM methods of FAHP, TOPSIS, and ELECTRE, purchasing managers can operationalize the Hill’s framework of order qualifier and winner that has primarily been used in the literature and manufacturing industry. This study represents the first move to innovatively apply the FAHP, TOPSIS, and ELECTRE methods to operationalize the Hill’s framework of order qualifier and winner that has primarily been used in the literature and manufacturing industry. Application to the fresh food industry to validate the feasibility of the proposed model has been conceived and implemented in this study. Analysis of the data inputs of a supermarket chain via the three MCDM methods generate the results that fulfill the purpose of achieving the research objective of identifying and managing the supplier base that can deliver the best supplier performance, conditional on first passing the fresh food safety test.

Accounting’s definition of accountability should include attributes of socioenvironmental degradation manufactured by unsustainable technologies. Beck argues that emergent accounts should reflect the following primary characteristics of technological degradation: complexity, uncertainty, and diffused responsibility. Financial stewardship accounts and probabilistic assessments of risk, which are traditionally employed to allay the public’s fear of uncontrollable technological hazards, cannot reflect these characteristics because they are constructed to perpetuate the status quo by fabricating certainty and security. The process through which safety thresholds are constructed and contested represents the ultimate form of socialized accountability because these thresholds shape how much risk people consent to be exposed to. Beck’s socialized total accountability is suggested as a way forward: It has two dimensions, extended spatiotemporal responsibility and the psychology of decision-making. These dimensions are teased out from the following constructs of Beck’s Risk Society thesis: manufactured risks and hazards, organized irresponsibility, politics of risk, radical individualization and social learning. These dimensions are then used to critically evaluate the capacity of full cost accounting (FCA), and two emergent socialized risk accounts, to integrate the multiple attributes of sustainability. This critique should inform the journey of constructing more representative accounts of technological degradation.

This study examines the relationship between fashion leadership, clothing deprivation and satisfaction of Hong Kong young consumers. A survey was carried out with 309 university students and 228 working young people in Hong Kong. Factor analysis with varimax rotation was used to group various attributes into different factors related to clothing deprivation and satisfaction. Hirschman and Adcock's (1978) measure was adopted to classify subjects into various fashion groups. ANOVA followed by Scheffe's procedure was applied to detect differences in clothing deprivation and satisfaction between different fashion groups. The implications of the findings to fashion retailers are discussed.

The use of behavioral insights and experimental methods has recently gained momentum among health policy-makers. There is a tendency, however, to reduce behavioral insights applications in health to “nudges,” and to reduce experiments in health to “randomized controlled trials” (RCTs). We argue that there is much more to behavioral insights and experimental methods in health economics than just nudges and RCTs. First, there is a broad and rich array of complementary experimental methods spanning the lab to the field, and all of them could prove useful in health economics. Second, there are a host of challenges in health economics, policy, and management where the application of behavioral insights and experimental methods is timely and highly promising. We illustrate this point by describing applications of experimental methods and behavioral insights to one specific topic of fundamental relevance for health research and policy: the experimental elicitation and econometric estimation of risk and time preferences. We start by reviewing the main methods of measuring risk and time preferences in health. We then focus on the “behavioral econometrics” approach to jointly elicit and estimate risk and time preferences, and we illustrate its state-of-the-art applications to health.

Whether or not a company is able to compete in the local and global arena depends significantly on how effectively the company can build up the partnership synergy with their business counterparts. With the emergence of a dispersed manufacturing network, the important issue is the criteria for the selection of the right partners for the right tasks. In this respect, it is essential to develop the necessary techniques to measure the performance of potential business partners prior to making the decision of partner selection. This paper suggests a performance measurement technique incorporated with on‐line analytical processing (OLAP) technology to support enterprise decisions related to selecting appropriate business partners. It also includes examples to illustrate how to apply this technique in real industrial situations.