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Within the competitive global market and fast-advancing technology environment, in order to survive and to succeed, firms need to spontaneously respond to market changes and the uncertainty of customer needs. Therefore, New Product Development (NPD) is extremely important for the success of firms. Artificial Intelligence (AI) has gradually entered people's lives, and consumer demand for AI products is increasing. Firms need to understand the AI development trend and consider the preferences of consumers for AI-related products under social changes so that suitable consumer AI products can be properly developed. In this study, the evaluation and selection of operation systems for a commercially available AI product (smart TV) is studied, and a Multi-Criteria Decision-Making (MCDM) model for facilitating the selection of the most suitable operation system for product development is constructed. The proposed model consists of three phases: Interpretative Structural Modelling (ISM) to construct a decision-making network, Fuzzy Analytic Network Process (FANP) to obtain the weights of factors, and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS) to rank the operation systems. The proposed model is applied to select an operation system that companies can use to develop a smart TV. The results show that the proposed model can provide a systematic method that helps companies make appropriate operation system selection decisions. [ABSTRACT FROM AUTHOR]

Assembly lines are often indispensable in factories, and a good assembly-line balancing model is very important for manufacturers to maximize their profit using limited resources in a competitive environment. To maintain a productive assembly line, multiple objectives with different importance must be considered at the same time. In this paper, a two-sided assembly-line balancing problem (TALBP) with multiple objectives is examined. A fuzzy multi-objective linear programming-weighted model (FMOLP-W) for solving the TALBP is constructed first with the consideration of the importance weights of the line balancing performance factors, including minimizing the number of workstations, minimizing cycle time, maximizing line efficiency, minimizing smoothness index and minimizing workstation idle time. An evolutionary genetic algorithm (GA) is proposed next to tackle large-scale problems when the problems are too complex to be solved by the FMOLP-W. [ABSTRACT FROM AUTHOR]

How to improve competitive edges to meet rapidly changing market environment and dynamic customer needs is critical for the survival and success of firms these days. A good supply chain and inventory management is a necessity in the intensive competitive market. This paper considers a dynamic-demand joint replenishment problem with multiple vehicle routing. The problem is first formulated as a mixed integer programming model with an objective to minimise total costs, which include ordering cost, purchase cost, production cost, transportation cost and holding cost, under a prerequisite that inventory shortage is prohibited in the system. A particle swarm optimisation model is proposed next to solve large-scale problems which are computationally difficult. A case study of a touch panel manufacturer is presented to examine the practicality of the models. [ABSTRACT FROM AUTHOR]

In recent years, the adoption of enterprise resource planning (ERP) is becoming essential for achieving fast and transparent information exchange, avoiding unnecessary waste and maintaining coordination within a firm and among partners in a supply chain. However, the implementation of an ERP system often fails, and one major reason is that the selected ERP system is not suitable for the firm. Therefore, a good evaluation framework for selecting the most appropriate ERP system is necessary. This study proposes a framework, which integrates decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) and fuzzy set theory, for the evaluation of ERP systems. First, the fuzzy DEMATEL is used to understand the direct and indirect relationships among the criteria. Second, the fuzzy ANP is adopted to calculate the importance weights of the sub-criteria. Finally, the most appropriate ERP system is obtained by the fuzzy VIKOR. The proposed decision-making framework is applied to a firm in the high-tech industry in selecting the most appropriate ERP system. The results show that the proposed framework can help firms evaluate ERP systems effectively by collecting experts' opinions in an uncertain environment. [ABSTRACT FROM AUTHOR]

Companies need to be innovative to survive in today's competitive market; thus, new product development (NPD) has become very important. This research constructs an integrated NPD framework for developing new products. In stage one, customer attributes (CAs) and engineering characteristics (ECs) for developing products are collected, and fuzzy interpretive structural modelling (FISM) is applied to understand the relationships among these critical factors. Based on quality function deployment (QFD), a house of quality is then built, and fuzzy analytic network process (FANP) is adopted to calculate the relative importance of ECs. In stage two, fuzzy failure mode and effects analysis (FFMEA) is applied to understand the potential failures of the ECs and to determine the importance of ECs with respect to risk control. In stage three, a goal programming (GP) model is constructed to consider the outcome from the FANP-QFD, FFMEA and other objectives, in order to select the most important ECs. Due to pollution and global warming, environmental protection has become an important topic. With both governments and consumers developing environmental consciousness, successful green and low-carbon NPD provides an important competitive advantage, enabling the survival or renewal of firms. The proposed framework is implemented in a panel manufacturing firm for designing a green and low-carbon product. [ABSTRACT FROM PUBLISHER]

Projects work under constant pressure of resource and time constraints. In order to perform effectively and efficiently, innovation seems to be a significant factor. However, due to the different nature of projects as compared to the organization, projects have been finding it difficult to undertake such innovation. However, ambidextrous innovation, which seeks to balance exploratory and exploitative innovation, offers a possible solution. However, research on the relationship between ambidextrous innovation and project management is at an early stage. The purpose of the present research is to undertake a systematic review of the literature to build and synthesize the understanding of innovation ambidexterity at the project level. Following the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) guidelines, our research collected data from the Web of Science and SCOPUS databases. By adhering to the PRISMA approach, we ensured a rigorous and transparent approach to the systematic review study, allowing for comprehensive data collection and analysis. The results of the present review study suggest that interest is building rapidly to incorporate ambidextrous innovation into project management. Ambidextrous innovation seemed to positively impact both the performance and capability of projects to undertake the innovation. Further, important drivers such as organizational culture, knowledge management, innovation activities, and agility play key roles in undertaking ambidextrous innovation at the project level. Further, elements of the team such as team integration, alignment, and knowledge utilization also play key roles. Finally, the avenue of future research has also been highlighted. [ABSTRACT FROM AUTHOR]

The prevalence of business-to-business (B2B) has made the relationship among firms more closer than ever. Whether in simple arm-length transactions or business cooperation, many firms, in order to reduce costs and achieve efficiency, have shifted their day-to-day operations from the tradition of relying on manpower to the use of information technology in handling tasks such as inventory, procurement, production planning, distribution, etc. As a result, the need of a business process information system is imminent for firms to coordinate with partners in the supply chain and to be sustainable in the competitive market. This study thus proposes a hybrid multi-criteria decision-making approach for evaluating business process information systems. First, the factors that should be taken into account in selecting an appropriate system are explored. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) is adopted next to understand the interrelationships among the criteria. Based on the results from the DEMATEL, the Fuzzy Analytic Network Process (FANP) is applied to calculate the importance of the factors. Fuzzy Techniques for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the business process information systems. The interrelationship among the factors should be considered in the decision-making; thus, the FANP can be a recommended methodology. However, the FANP questionnaire is usually very lengthy and cumbersome. The use of DEMATEL in advance can shorten the questionnaire substantially. FTOPSIS is used to rank the alternatives so that the pairwise comparisons of the alternatives required in the FANP can be avoided. Fuzzy set theory is incorporated in the study so that the uncertainty and ambiguity present in decision-making can be considered. The proposed approach can provide references for decision makers for making relevant decisions and can be revised and adopted in similar problems. [ABSTRACT FROM AUTHOR]

The benefits, opportunities, costs, and risks (BOCR) model is a multiple-criteria decision-making (MCDM) model used to elicit a mutually exclusive and collectively exhaustive set of criteria. As an acronym proposed in the theory of the analytic hierarchy process (AHP), the BOCR model has received attention from users of this MCDM method. A state-of-the-art review, an approach to a literature review that is more comprehensive than a rapid review but not as exhaustive as a systematic literature review, was performed with the Scopus database. The overwhelming majority of documents found on BOCR were practical applications, but they were from diverse areas, including business, computer science, and engineering. It is proposed that two main kinds of contributions for future research on BOCR should be methodological and practical. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce a heuristic approach that uses a capacitated inventory model as means for identifying a collaborative agreement between different buyers jointly replenishing multiple items from multiple vendors, thus attaining economies of scale while reducing by sharing fixed procurement and operational costs. The proposed approach is denominated Stochastic Collaborative Joint Replenishment Problem (S-CJRP) and consists of two stages. The first stage determines a cost-efficient replenishment frequency for each collaborating company in all possible coalition arrangements. To accomplish the former, an extension of the known Joint Replenishment Problem (JRP) considering real-life capacity constraints, such as stochastic demand assuming normal distribution, finite storage and transport, is solved via genetic algorithms delivering a suitable coalition. In a second stage, the Shapley Value function is established to assess and allocate the potential gains achieved by colluding in the first stage, determining a fair share distribution among players that increases the viability of such coalition. Several scenarios from a simulated numerical study illustrate average cost savings of 32.3%. 28.2% and 32.7% for 3, 4 and 5 players, respectively, considering up to 30 items for the proposed collaboration, in all cases consistently exhibiting cost reduction and increasing the proposal feasibility. [ABSTRACT FROM AUTHOR]

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We examine a coordinated capacitated lot-sizing problem for multiple product families, where demand is deterministic and time-varying. The problem considers set-up and holding costs, where capacity constraints limit the number of individual item and family set-up times and the amount of production in each period. Using a strong reformulation and relaxing the demand constraints, we improve both the upper and lower bounds using a combination of Benders decomposition and an evolutionary algorithm, followed by subgradient optimisation. Through computational experiments, we show that our method consistently achieves better bounds, reducing the duality gap compared to other single-family methods studied in the literature. [ABSTRACT FROM AUTHOR]

In many supply chain scenarios in which short lifespan products are considered, production and transportation decisions must be made in a coordinated manner with no inventory stage. Hence, a solution to this problem conveys information about production starting times of each product lot at facility and delivery times of the lots to various customer-sites located in different geographic regions. In this paper, we study a variant of the problem that single product with limited shelf life is produced at single facility. Once produced, production lot is directly distributed to the customers with non-ignorable transportation time by single vehicle having limited capacity before the lifespan. Objective is to determine the minimum time required to produce and deliver all customer demands. To this end, we develop a branch-and-cut (B&C) algorithm using several valid inequalities adopted from the existing literature to improve lower bounds and applying a local search based on simulated annealing approach to improve upper bounds. On test problems available in the literature, we evaluate the performance of the B&C algorithm. Results show the promising performance of the B&C algorithm. [ABSTRACT FROM AUTHOR]

Integrating production scheduling with transportation decisions is an important problem that is receiving increasing interest from the logistics industry. As an order is received, the manufacturer starts planning its production while considering the appropriate decisions for delivery. The company can adopt an auction paradigm to involve external occasional drivers, besides using its own fleet for the delivery. Ahead of an auctioning process, the company should decide which deliveries should be served by its fleet and which can be assigned to the occasional drivers. This is known as the shipper lane selection problem (SLSP). This article integrates the SLSP with production scheduling and proposes an integer formulation and heuristic methods to solve the resulting integrated problem (I-SLSPS). Experiments show the validity of the proposed methods and their capability in achieving minimum cost for the integrated problem. [ABSTRACT FROM AUTHOR]

A list of reviewers for the "International Journal of Production Research" is presented including Amin Aalei, Kerem Akartunali and Serap Akcan.

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions. [ABSTRACT FROM AUTHOR]

In this paper, we define the idea of cubic linguistic uncertain fuzzy numbers. We define the idea of triangular cubic linguistic uncertain fuzzy number. We discuss some basic operational laws of triangular cubic linguistic uncertain fuzzy number and hamming distance of TCLUFNs. We introduce the new concept of triangular cubic linguistic uncertain fuzzy TOPSIS method. Furthermore, we extend the classical triangular cubic linguistic uncertain fuzzy TOPSIS method to solve the MCDM method based on triangular cubic linguistic uncertain fuzzy TOPSIS method. The new ranking method for TCLUFNs is used to rank the alternatives. Finally, an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The article lists the reviewers of the journal including Henry Abanda, George Adamson and Andrew Allan.

Copyright of Optimum: Journal of Economics & Management Sciences / Ekonomi ve Yönetim Bilimleri Dergisi is the property of Optimum: Journal of Economics & Management Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)