Strategic information systems contribute to enhance managerial understanding in terms of organisational development and business success. In particular, they assist in making timely business decisions and formulating feasible strategic plans. In practice, a strategic information system consists of several modules performing different functions such as strategic prerequisites, strategic directions and so forth. The integration of these modules to form a unified system is an essential task for achieving an efficient as well as effective strategic information system. In today's business environment, where there are a great variety of standards in various computer systems that make the linking of modules to enable bi‐directional electronic data interchange difficult and costly. This paper attempts to introduce a model which embraces a neutral format approach to realise the efficient and reliable information flow among various modules of a strategic information system. Furthermore, the proposed guidelines for implementing such a system using the neutral format generalisation technique are also covered.
Purpose – When making sourcing decisions, both cost optimization and customer demand fulfillment are equally important for firm competitiveness. The purpose of this paper is to develop a stochastic search technique, hybrid genetic algorithm (HGA), for cost-optimized decision making in wholesaler inventory management in a supply chain network of wholesalers, retailers and suppliers.
Design/methodology/approach – This study develops a HGA by using a mixture of greedy-based and randomly generated solutions in the initial population and a local search method (hill climbing) applied to individuals selected for performing crossover before crossover is implemented and to the best individual in the population at the end of HGA as well as gene slice and integration.
Findings – The application of the proposed HGA is illustrated by considering multiple scenarios and comparing with the other commonly adopted methods of standard genetic algorithm, simulated annealing and tabu search. The simulation results demonstrate the capability of the proposed approach in producing more effective solutions.
Practical implications – The pragmatic importance of this method is for the inventory management of wholesaler operations and this can be scalable to address real contexts with multiple wholesalers and multiple suppliers with variable lead times.
Originality/value – The proposed stochastic-based search techniques have the capability in producing good-quality optimal or suboptimal solutions for large-scale problems within a reasonable time using ordinary computing resources available in firms.
Purpose 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.
Design/methodology/approach 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.
Findings 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.
Practical implications 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.
Originality/value 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.
Purpose Despite much research on supply chain (SC) integration and the growing emphasis on recent information technology advancements as an enabler of improved performance, there has been limited research focussed specifically on information integration in supply chains (SCs). The purpose of this paper is to systematically review the literature on information integration in the fresh food supply chain (FFSC) from a holistic perspective.
Design/methodology/approach Literature review is done by systematically collecting and analysing the recent literature to identify various participant entities of the FFSC information network and their specific information needs.
Findings The information needs of FFSC entities are diverse but the needs are common across multiple entities.
Research limitations/implications This study only reviewed the FFSC-related literature; an extended study of the food industry may reveal a more comprehensive view.
Practical implications These findings are useful for practitioners in understanding the participant entities in the information network and their information needs and for policymakers in formulating FFSC development initiatives.
Originality/value The authors are not aware of another study that investigates the FFSC in a holistic approach, one that identifies the actors, their interactions and information needs.
Purpose – As a response to increasing global market competition, companies in various industries tend to identify and manage customer relationship to increase profit performance. Companies commit more resources to identify their VIP customers and retain them by all means. The purpose of this paper is to develop a customer relationship management (CRM) business process management (BPM) model to identify airline customers with different degree of relationship and profit potential, and select the highly profitable customers for developing retention strategy and processes, and convert the less profitable into profitable corporate accounts.
Design/methodology/approach – This study innovatively apply the well-known techniques including CRM and relationship marketing models, fuzzy analytic hierarchy process (FAHP), and technique for order preference by similarity to ideal solution (TOPSIS) in the BPM research. This novel approach analyzes longer term customer profit and value potential, and prioritizes corporate accounts as the basis for setting appropriate customer service levels and improving the CRM process. This hybrid model is able to capitalize on the benefits of these methods and offset their deficiencies. Most importantly, it can be customized to various industries without complex modification.
Findings – This study uses data of an airline company to validate feasibility of the proposed CRM BPM model. The results indicate that this model is able to classify the customers based on various criteria and sub-criteria, thus allowing companies to introduce appropriate service levels to deal with different categories of customers, and improve CRM process so as to maximize customer profit and value potential.
Practical implications – This CRM BPM model and analysis provide managers extensive customer knowledge, more analytical and fact-based decision-making support, and a stronger focus on return on investment in sales and marketing. Knowing the profit and value potential generated by individual corporate customer makes it easier to establish the link between the CRM and the profit outcome. This model also benefits the organization and its stakeholders by allocating more resources to the targeted customer relationships that are profitable or valuable, and makes marketing more accountable in its marketing programs.
Originality/value – This study makes the first move to innovatively apply the well-known techniques including CRM and relationship marketing models, FAHP, and TOPSIS in the BPM research.
A typical product design project involves a number of activities, and each activity requires human resources support. These activities and resources must be properly planned and scheduled in order to achieve optimum project time and cost. This paper proposes a process planning and scheduling (PPAS) system which is based on the concept of process planning typically used for the planning of production activities. Object technology (OT) is chosen as the platform for the development of the PPAS model for its specific characteristics such as inheritance, encapsulation, polymorphism etc. Presents the concept of the PPAS system, discusses its relationship with reference to product design, and proposes the use of object technology as a platform for building the PPAS.
AbstractScope 3 emissions evaluation is a challenge but Walmart's collaborations with its suppliers has set the benchmark as they successfully reported these emissions to Carbon Disclosure Project in 2020. This study has analysed Walmart's best supplier management practices (The sustainability insight system or THESIS, Project gigaton and Blockchain technology) that proved their success in identifying, evaluating and reducing scope 3 emissions. Using Agribalyse database and case product of beef pie, we identified critical hotspots in upstream food supply chains through life cycle assessment (LCA). A weighting method was used to prioritise the critical hotspots. For empirical evidence, a few hotspots were addressed using Walmart's best practices and modified LCA was piloted that showed up to 10% decreased environmental burden, irrespective of the change in region, data mix and supply chain complexity. For industrial implication, a hotspot resolution model was designed for the root cause analysis of pain points concerning global food supply chains. Firms can use this generic model to identify and implement best practices based on breakdown of supply chain hotspots.
