PurposeThis study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research covered the data on the said topic since it first originated in the Scopus database and carried out performance analysis and content analysis of papers in the business management and finance disciplines.Design/methodology/approachBibliometric analysis, including science mapping and performance analysis, followed by content analysis of the papers of identified clusters, was conducted. Three clusters based on cocitation analysis and six themes (three major and three minor) were identified using the bibliometrix package in R studio. The content analysis of the papers in these clusters and themes have been discussed in this study, along with the thematic evolution of intertemporal choice research over the period of time, paving a way for future research studies.FindingsThe review unpacks publication and citation trends of intertemporal choice behavior, the most significant authors, journals and papers along with the major clusters and themes of research based on cocitation and degree of centrality and relevance, respectively, i.e. discounting experiments and intertemporal choice, impulsivity, risk preference, time-inconsistent preference, etc.Originality/valueOver the past years, the research on “intertemporal choice” has flourished because of the increasing interest of researchers and scholars from different fields and the dynamic and pervasive nature of this topic. The well-developed and scattered body of knowledge on intertemporal choice has led to the need of applying a bibliometric analysis in the intertemporal choice literature.

PurposeThis paper aims to propose an integrated use of balanced scorecard (BSC), data envelopment analysis (DEA) and game theory approach as an enhanced performance measurement technique to determine and rank the importance of manufacturing indicators of a steel company as a real case study.Design/methodology/approachAn efficiency change ratio is defined to examine the characteristic function of each coalition which is super-additive. Then, the Shapley value index is used as the solution of the cooperative game to determine the importance of the BSC indicators of the company and rank order them.FindingsThe results reveal that “profitability rate” is the most important BSC indicator, whereas “customer satisfaction” is the least significant one. The ranking order of the importance of all BSC indicators makes it possible for the senior managers of the organization to realize the importance of each index separately and to improve the profitability and the number of customers by presenting programs according to the budget and time constraints.Originality/valueThe main contribution of this paper lies in the adoption of a game theory approach to performance measurement in the industrial sector that determines and ranks the importance of manufacturing indicators.

PurposeSmall and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.Design/methodology/approachA multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.FindingsSLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.Research limitations/implicationsThis work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.Practical implicationsThe generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.OriginalityThe sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.

PurposeThis paper aims to examine the optimal sourcing strategies and pricing decisions of competing toy manufacturers and to discuss how manufacturers’ decisions are impacted by competition.Design/methodology/approachThe authors consider a single-period model to characterise the competition between two competing toy manufacturers. Both of them are free to choose between virgin material and recycled material. The authors consider two types of consumers: sensitive consumers who are concerned about product safety and prefer the toy made of virgin material and insensitive consumers who do not care what material is used in the toy. The competing manufacturers play a Cournot competition.FindingsThe results reveal a special case of a win-win situation for both the manufacturer and the consumer. In addition, an increasing number of sensitive consumers does not always raise the price of virgin-material toys.Practical implicationsThe authors derive the manufacturer’s equilibrium sourcing strategies, corresponding market-clearing prices and profits obtained.Originality/valueThe paper investigates how toy manufacturers’ optimal sourcing strategies are impacted by competition, considering market segments.

PurposeThis paper aims to propose an improved version of portfolio optimization model through the prediction of the future behavior of stock returns using a combined wavelet-based long short-term memory (LSTM).Design/methodology/approachFirst, data are gathered and divided into two parts, namely, “past data” and “real data.” In the second stage, the wavelet transform is proposed to decompose the stock closing price time series into a set of coefficients. The derived coefficients are taken as an input to the LSTM model to predict the stock closing price time series and the “future data” is created. In the third stage, the mean-variance portfolio optimization problem (MVPOP) has iteratively been run using the “past,” “future” and “real” data sets. The epsilon-constraint method is adapted to generate the Pareto front for all three runes of MVPOP.FindingsThe real daily stock closing price time series of six stocks from the FTSE 100 between January 1, 2000, and December 30, 2020, is used to check the applicability and efficacy of the proposed approach. The comparisons of “future,” “past” and “real” Pareto fronts showed that the “future” Pareto front is closer to the “real” Pareto front. This demonstrates the efficacy and applicability of proposed approach.Originality/valueMost of the classic Markowitz-based portfolio optimization models used past information to estimate the associated parameters of the stocks. This study revealed that the prediction of the future behavior of stock returns using a combined wavelet-based LSTM improved the performance of the portfolio.

PurposeA reconfigurable manufacturing system (RMS) can provide manufacturing flexibility, meet changing market demands and deliver high performance, among other benefits. However, adoption and performance improvement are critical activities in it. The current study aims to identify the important factors influencing RMS adoption and validate a conceptual model as well as develop a structural model for the identified factors.Design/methodology/approachAn extensive review of RMS articles was conducted to identify the eight factors and 47 sub-factors that are relevant to RMS adoption and performance improvement. For these factors, a conceptual framework was developed as well as research hypotheses were framed. A questionnaire was developed, and 117 responses from national and international domain experts were collected. To validate the developed framework and test the research hypothesis, structural equation modeling was used, with software tools SPSS and AMOS.FindingsThe findings support six hypotheses: “advanced technologies,” “quality and safety practice,” “strategy and policy practice,” “organizational practices,” “process management practices,” and “soft computing practices.” All of the supported hypotheses have a positive impact on RMS adoption. However, the two more positive hypotheses, namely, “sustainability practices” and “human resource policies,” were not supported in the analysis, highlighting the need for greater awareness of them in the manufacturing community.Research limitations/implicationsThe current study is limited to the 47 identified factors; however, these factors can be further explored and more sub-factors identified, which are not taken into account in this study.Practical implicationsManagers and practitioners can use the current work’s findings to develop effective RMS implementation strategies. The results can also be used to improve the manufacturing system’s performance and identify the source of poor performance.Originality/valueThis paper identifies critical RMS adoption factors and demonstrates an effective structural-based modeling method. This can be used in a variety of fields to assist policymakers and practitioners in selecting and implementing the best manufacturing system.Graphical abstract

PurposeThe purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design.Design/methodology/approachThe study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies.FindingsThe results of the study present the researchers’ tendencies and preferences when designing their BSC network models.Research limitations/implicationsThe study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs.Originality/valueThe study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.

PurposeThis study aims to examine the value of the call option contract in hedging the risks in the supply chain. The decentralized supply chain without call option contract is first studied as the criterion model for evaluations. This paper addresses several questions: What will be the optimal manufacturer’s production quantity, retailer’s ordering and pricing policies in the presence of random demand and random yield by applying the downconversion approach? How will the call option contract influence the optimal decisions for the members of the supply chain? Can the risk from randomness be divided among the members in the supply chain through the call option contract?Design/methodology/approachThis paper considers a two-level decentralized supply chain under random yield and random demand in which the manufacturer takes advantage of the downconversion approach with two scenarios, with and without option contract. To the best of the authors’ knowledge, no article or study uses the downconversion approach in a supply chain regarding random yield and random demand. Furthermore, the paper considers pricing with option contract in the supply chain, which makes this article stands out significantly from other articles in the literature.FindingsThis study shows that the downconversion approach would reduce the risk caused by the random yield, which appears to be the appropriate method for the environmental goal of the supply chains. Moreover, adopting a call option contract can increase flexibility and mitigate risks, resulting in more expected members’ profits.Research limitations/implicationsTo simplify the model, the authors assume one manufacturer and one retailer, so extending the model to consider multiple retailers instead of one retailer and inventory sharing between them would be interesting. Considering the option and exercise prices as decision variables would be important future research topics. Put option and bidirectional option contracts could be investigated in the future. Another extension is modeling asymmetry of information in supply chain.Originality/valueThis paper provides managerial insights on dealing with both demand and yield risks in a manufacturer–retailer supply chain. The manufacturer has a random yield production and produces two types of vertical products: low-end and high-end. To reduce waste caused by the random yield, the manufacturer uses a downconversion approach in which low-end products are made by converting the defective high-end products. The manufacturer purchased a shortage of high-end products from the secondary market (i.e. emergency sourcing). High-end products are sold through the retailer, and low-end products are sold directly by the manufacturer. The customer demand for high-end products in the end market is random and depends on the selling price, and the customer demand for the low-end products in the secondary market is independent and random. The retailer contracts the manufacturer with the call option to obtain high-end products to meet a random demand; in fact, by using the call option contract, the authors try to balance the risks between two members. Two scenarios of with and without call option contract are proposed. After the high-end product demand is observed, the retailer would exercise the option order quantity in the call option contract scenario and then place an instant order with the manufacturer if necessary. In each scenario, the manufacturer and the retailer make their decisions simultaneously (static game) to determine the retailer’s optimal ordering and pricing policies and the optimal production quantity of the manufacturer (Nash equilibrium) by maximizing their expected profits. Finally, the impact of the model parameters on the supply chain is expressed through numerical examples. The numerical analysis shows that the call option contract provides greater profit than the wholesale price contract.

PurposeAirline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling strategy is vital for a commercial airline. The purpose of this paper is to present an integrated aircraft and crew recovery plans to reduce delay and prevent delay propagation on airline schedule with the minimum cost.Design/methodology/approachA mixed-integer linear programming model is proposed to formulate an integrated aircraft and crew recovery problem. The main contribution of the model is that recovery model is formulated based on individual flight legs instead of strings. This leads to a more accurate schedule and better solution. Also, some important issues such as crew swapping, reassignment of aircraft to other flights as well as ground and sit time requirements are considered in the model. Benders’ decomposition approach is used to solve the proposed model.FindingsThe model performance is also tested by a case including 227 flights, 64 crew, 56 aircraft and 40 different airports from American Airlines data for a 24-h horizon. The solution achieved the minimum cost value in 35 min. The results show that the model has a great performance to recover the entire schedule when disruption happens for random flights and propagation delay is successfully limited.Originality/valueThe authors confirm that this is an original paper and has not been published or under consideration in any other journal.

PurposeThis paper aims to present two-stage network models in the presence of stochastic ratio data.Design/methodology/approachBlack-box, free-link and fix-link techniques are used to apply the internal relations of the two-stage network. A deterministic linear programming model is derived from a stochastic two-stage network data envelopment analysis (DEA) model by assuming that some basic stochastic elements are related to the inputs, outputs and intermediate products. The linkages between the overall process and the two subprocesses are proposed. The authors obtain the relation between the efficiency scores obtained from the stochastic two stage network DEA-ratio considering three different strategies involving black box, free-link and fix-link. The authors applied their proposed approach to 11 airlines in Iran.FindingsIn most of the scenarios, when alpha in particular takes any value between 0.1 and 0.4, three models from Charnes, Cooper, and Rhodes (1978), free-link and fix-link generate similar efficiency scores for the decision-making units (DMUs), While a relatively higher degree of variations in efficiency scores among the DMUs is generated when the alpha takes the value of 0.5. Comparing the results when the alpha takes the value of 0.1–0.4, the DMUs have the same ranking in terms of their efficiency scores.Originality/valueThe authors innovatively propose a deterministic linear programming model, and to the best of the authors’ knowledge, for the first time, the internal relationships of a two-stage network are analyzed by different techniques. The comparison of the results would be able to provide insights from both the policy perspective as well as the methodological perspective.