Showing papers in "Journal of Modelling in Management in 2017"

Inventory model in a four-echelon integrated supply chain: modeling and optimization

Abstract: The main purpose is to minimize the total inventory cost of chain, whereas the stochastic constraints are satisfied. In other words, the goal is to find optimum agreed stockpiles and period length for products to minimize the total inventory cost of the chain while the stochastic constraints are fulfilled.,This paper designs and optimizes an integrated inventory model in a four-echelon supply chain that contains a supplier, a producer, a wholesaler and multiple retailers. All four levels agree with each other to make an integrated inventory system. Products in this model have a multi-stage production process, and the model is bounded by multiple stochastic constraints. The problem model is nonlinear and large. So, the interior point method as an effective algorithm is used for solving the recent convex nonlinear model. Two numerical examples are solved to demonstrate the application of this methodology and to evaluate the performance of the proposed approach.,The findings showed the model is applicable for real-world supply chain problems in the cases that echelons are going to do executive external integration. Also, the Interior Point algorithm has a satisfactory performance and a high efficiency in terms of optimum solution for solving nonlinear and large models.,The authors designed and optimized the inventory cost in a four-level integrated supply chain in stochastic conditions. The new decision variables, number of chain levels, multi-products, stochastic constraints and multi-stage products in four-level integrated supply chain are other novelties of this paper. The authors provided an efficient algorithm for solving a large-scale and nonlinear model in this research, too.

Analyzing enablers of sustainable supply chain: ISM and fuzzy AHP approach

Abstract: Purpose This paper aims to intend to help focal firms which are keen to develop a sustainable supply chain by identifying enablers, in knowing the interrelationships involved and in ranking the enablers. Design/methodology/approach Interpretive structural modeling and fuzzy MICMAC were used for the modeling and clustering of the enablers and fuzzy analytical hierarchy process has been used for the ranking purpose. Findings Awareness about sustainability incentives, pressure from stakeholders, support from supply chain partners and demand from customer for sustainable products were found very important for developing a sustainable supply chain. Research limitations/implications This research will help practitioners to appreciate the importance of the enablers to focus on the making sustainability adoption feasible across the supply chain. This would also facilitate focal firm management to develop a sustainability culture across the supply chain. Originality/value Similar work has not been carried before in which interaction among enablers and their priorities were analyzed using hybrid methodologies in developing country context.

Sensibility analysis of MCDA using prospective in Brazilian energy sector

Abstract: Purpose The purpose of this paper is to present a hybrid modelling that combines concepts and techniques for scenario building together with a Multi-criteria Decision Aid (MCDA) outranking approach. The paper presents a case to illustrate the proposed methodology. Design/methodology/approach The research method is a qualitative and quantitative mixture and it is presented as a study case. Bibliographic research is used to construct the theoretical framework. There are a number of studies that develop a sensibility analysis in MCDA modelling; however, none of them explore the robustness of the MCDA solution with use of scenarios variation. Findings The methodology allows the criteria that must be taken into account, according to the decision makers’ values and preferences. It is interesting to note that, depending on the scenario, different weights were applied for each criterion, and the performances of alternatives under each criterion has changed as well. Practical implications This need arises in decision problems that are susceptible to the influence of scenario variation. Originality/value This proposal was applied to a real case that has taken into account six alternatives, with a prospective analysis of three scenarios, evaluated by four criteria. The authors use prospective scenarios to choose the criterion weights and alternatives evaluation.

Environmentally concerned consumer behavior: evidence from consumers in Rajasthan

Abstract: This study aims to empirically indicate that environment-friendly products may be used as a consumption strategy for improving the environmental well-being of a sizable consumer base and show that there are great possibilities and opportunities available for companies to come up with the right marketing mix for consumers in the rural market. There is a great dearth of empirical research on consumer behavior facets on environment-friendly products for rural market in India.,Conclusive cross-sectional descriptive research design has been used to study the environmentally concerned consumer behavior (ECCB) for environment-friendly products with the help of a survey instrument relevant for empirical research. This paper adds to the existing literature by developing one model in the Indian context for the rural market. The research study used exploratory factor analysis and confirmatory factor analysis with structural equation modeling approach to analyze the collected data from consumers.,The major finding of the study is that consumers living in rural areas are aware about the environmental movement, but marketers have probably not fully explored the potential for environment-friendly products. The study strongly argues that organizations should leverage on the rural market opportunity in India. It confirms the need to tailor marketing mix for rural markets for determining behavioral dimensions of consumer decision-making.,This empirical research paper is developed and applied in the Indian context, with special reference to the rural market of the country. Results may change when applied to different rural locations in the same country and/or different countries depending on their demographic variables, psychosocial factors and socioeconomic conditions. The findings of this study need to be viewed within the context of certain limitations of location, social and economic issues. The study provides the initial base for further research on the theme, as there are no such studies available on environment-friendly products.,This research study is highly useful for the business firms deciding on marketing mix variables for environment-friendly products in rural market scenario in India, and it provides inputs for formulating major policy decisions in marketing. The study provides insights for managers, policymakers and organizations operating in rural markets and working on different facets of environmental protection issues in different forms.,It has been investigated across global markets that human activities have altered the natural ecosystem, so to make natural resources available for the future generation, there is a greater need to achieve more sustainable forms of development. The study provides insights from the rural Indian market for better adoption of environment-friendly products and will motivate marketers to explore the rural market horizon.,The study has been conducted with consumers who are residents of one small town in India. So far, no study has been conducted, and it is first such attempt to analyze the rural Indian market for environment-friendly products and consumer behavior ever since such products were launched in the country. This study provides an early glimpse into the workings of marketing practitioners who work on consumer strategy formulation and rural marketing decision-making for environment-friendly products.

An ISM-based approach analyzing interactions among variables of reverse logistics in automobile industries

Abstract: Purpose This paper aims to analyze the interaction among the major variables of reverse logistics seen in automobile industries. Design/methodology/approach In this research, interpretive structural modeling (ISM) has been used to understand mutual influences among identified variables of reverse logistics. The advantage of the ISM methodology is that variables can be categorized depending upon their driving power and dependence. Findings Regulations make it mandatory for automobile companies to own responsibility of products manufactured throughout their life cycle by collecting and reusing products, reducing volume of waste generated, increasing the use of recycled materials, etc. For example, End-of-Life Vehicle Directive had directed manufacturers to take back their vehicles at the end of their usefulness and responsibly dispose them. In this research, regulation has appeared at bottom of the ISM model, indicating that it has high driving power to influence other variables. Also, financial limitations are a significant inhibitor faced by the top management for implementing reverse logistics programs. Research limitations/implications The ISM methodology relies upon expert opinions for developing contextual relation among identified variables. Thus, an expert’s knowledge, his familiarity with industry and its operations may have affected the final results of the ISM model. One of research implications of this study is that variables identified in this ISM model are quite generic, and thus, with marginal adjustments, these can be used in the context of any other supply chain for increasing its productivity and performance. Practical implications The ISM model reveals that regulations affect a significant number of enabler variables of reverse logistics like support of policy entrepreneurs, green purchasing by companies, information and communication technologies that are seen at the upper level of ISM. This indicates that regulations force companies to be proactive towards product recovery actions that lead to initiation of reverse logistics programs by them. Originality/value This research has tried to analyze the interaction among the major variables of reverse logistics typically seen in automobile industries which could be useful to logistics managers for taking strategic-level decisions.

Modeling the key barriers to lean construction using interpretive structural modeling

Abstract: Purpose The purpose of this study is to identify and analyze the key barriers to lean implementation in the construction industry using interpretive structural modeling (ISM) and Matrice d’ Impacts Croises-Multiplication Appliquee a un Classement (MICMAC) analysis. Design/methodology/approach In this study, 13 barriers to lean construction (LC) have been identified through extensive review of literature and subsequently eliciting expert opinions. A proper hierarchy and contextual relationship of the barriers have been developed using ISM, and based on the driving and dependence power of the barriers, three groups of barriers have been found using MICMAC analysis. Findings Cultural differences are found to be the most important barrier to LC, whereas employees’ resistance to change and lack of performance measurement systems are the least significant barriers. Research limitations/implications The work is limited to literature review and experts’ opinion, and the model may be tested using structural equation modeling to verify the relationship of the barriers. Practical implications This ISM-based model would help the decision-makers, researchers and practitioners to prioritize and manage these barriers by better utilizing their resources for eliminating or minimizing the barriers to lean implementation. Originality/value The study of barriers to LC through an ISM-based model and the classification of barriers is a new attempt in the field of construction.

Decision support systems in manufacturing: a survey and future trends

Abstract: Purpose This paper aims to propose a theoretical decision support framework, which integrates artificial intelligence (AI), discrete-event simulation (DES) and database management technologies so as to determine the steady state flow of items (e.g. fixtures, jigs, tools, etc.) in manufacturing. Design/methodology/approach The existing literature was carefully reviewed to address the state of the arts in decision support systems (DSS), the shortcomings of pure simulation-based and pure AI-based DSS. A conceptual example is illustrated to show the integrated application of AI, simulation and database components of the proposed DSS framework. Findings Recent DSS studies have revealed the limitations of pure simulation-based and pure AI-based DSS. A new DSS framework is required in manufacturing to address these limitations, taking into account the problems of flowing items. Research limitations/implications The theoretical DSS framework is proposed using simple rules and equations. This implies that it is not complex for software development and implementation. Practical data are not presented in this paper. A real DSS will be developed using the proposed theoretical framework and realistic results will be presented in the near future. Originality/value The proposed theoretical framework reveals how the integrated components of DSS can work together in manufacturing in order to determine the stable flow of items in a specific production period. Especially, the integrated performance of case-based reasoning (CBR) and DES is conceptually illustrated.

Exploring Big Five personality traits and gender as predictors of entrepreneurs’ cognitive adaptability

Abstract: Purpose The purpose of this study was to explore the predictive role of personality and gender in cognitive adaptability of entrepreneurs. By using the theories of personality development, social learning, situated cognition and meta-cognition, a logical relationship between personality traits, gender difference and entrepreneurs’ cognitive adaptability was established. Design/methodology/approach Quantitative strategy and cross-sectional survey method was then deployed to empirically investigate the purposed relationships between variables of interest. Randomly selected 443 working entrepreneurs responded to the survey. Findings Factor analyzed structural equation modeling estimated cognitive adaptability as a second-order factor, with extroversion and neuroticism having a significant impact on cognitive adaptability. Multi-group moderation revealed a significant difference among females and males against the same two personality traits. Originality/value This study in its nature is the first attempt to link Big Five personality traits with cognitive adaptability of entrepreneurs.

Dynamic capabilities and their impact on research organizations’ R&D and innovation performance

Abstract: Purpose The purpose of this paper is to reveal and justify influential factors of dynamic capabilities on research organizations’ R&D and innovation performance. Design/methodology/approach Adoption of seminal D. Teece’s (1997) concept of dynamic capabilities and operationalized matrix of key performance indicators in the area of R&D and innovation allowed the construction of the strategic management model for research organizations, consequently tested by methods of statistical analysis. Findings The empirical findings reveal that there exists positive influence of the dynamic capabilities on research organizations’ RD consequently, the peculiarities of their inter-dependencies are identified. Research limitations/implications Delivered research is based on the investigation of Lithuanian research organizations’ dynamic capabilities and their impact on their R&D and innovation performance. Therefore, further research could be extended to foreign countries. Practical implications The model on management of research organization’s dynamic capabilities with the aim for better R&D and innovation performance is conceptualized and specified hereinafter. In the course of the research, constructed toolkit to eventually measure research organization’s R&D and innovation performance or use it as the set of key performance indicators in the benchmarking exercise is suggested. Originality/value The paper is one of the first to suggest novel application of dynamic capabilities’ view within the domain of research organizations.

Evaluation of success factors for medical device development using grey DEMATEL approach

Abstract: Purpose Successful device development brings substantial revenues to medical device manufacturing industries. This paper aims to evaluate factors contributing to the success of medical device development (MDD) using grey DEMATEL (decision-making trial and evaluation laboratory) methodology through an empirical case study. Design/methodology/approach The factors are identified through literature review and industry experts’ opinions. Grey-based DEMATEL methodology is used to establish the cause-effect relationship among the factors and develop a structured model. Most significant factors contributing to the success of MDD are identified. An empirical case study of an MDD and manufacturing organisation is presented to demonstrate the use of the grey DEMATEL method. Sensitivity analysis is carried out to check robustness of results. Findings The results of applying the grey DEMATEL methodology to evaluate success factors of MDD show that availability of experts and their experience (SF4) is the most prominent cause factor, and active involvement of stakeholders during all stages of MDD (SF3) and complete elicitation of end-user requirements (SF1) are the most prominent effect factors for successful MDD. A sensitivity analysis confirms the reliability of the initial solution. Practical implications The findings will greatly help medical device manufacturers to understand the success factors and develop strategies to conduct successful MDD processes. Originality/value In the past, few success factors to MDD have been identified by some researchers, but complex inter-relationships among factors are not analysed. Finding direct and indirect effects of these factors on the success of MDD can be a good future research proposition.

Supply chain scheduling and routing in multi-site manufacturing system (case study: a drug manufacturing company)

Abstract: Purpose This study aims to propose a new genetic algorithm for solving supply chain scheduling and routing problem in a multi-site manufacturing system. The main research question is: How is the production and transportation scheduled in a multi-site manufacturer? Also the sub-questions are: How is the order assigned to the suppliers? What is the production sequence of the assigned orders to a supplier? How is the order assignment to the vehicles? What are the vehicles routes to convey the orders from the suppliers to the manufacturing centers? The authors’ contributions in this paper are: integration of production scheduling and vehicle routing in multi-site manufacturing supply chain and proposing a new genetic algorithm inspired from the role model concept in sociology. Design/methodology/approach Considering shared transportation system in production scheduling of a multi-site manufacturer is investigated in this paper. Initially, a mathematical model for the problem is presented. Afterwards, a new genetic algorithm based on the reference group concept in sociology, named Reference Group Genetic Algorithm (RGGA) is introduced for solving the problem. The comparison between RGGA and a developed algorithm of literature closest problem, demonstrates a better performance of RGGA. This comparison is drawn based on many test problems. Moreover, the superiority of RGGA is certificated by comparing it to the optimum solution in the small size problems. Finally, the authors use real data collected from a drug manufacturer in Iran to test the performance of the algorithm. The results show the better performance of RGGA in comparison with obtained outputs from the real case. Findings The authors presented the mathematical model of the problem and introduced a new genetic algorithm based on the “reference group” concept in sociology. Robert K. Merton is a sociologist who presented the concept of reference groups in society. He believed that some people in each society such as heroes or entertainment artists affect other people. The proposed algorithm uses the reference group concept to the genetic algorithm, namely, RGGA. The comparison of the proposed algorithm with DGA and the optimum solution shows the superiority of RGGA. Finally, the authors implement the algorithm in a real case of drug manufacturing and the results show that the authors’ algorithm gives better outputs than obtained outputs from the real case. Originality/value One of the major objectives of supply chains is to create a competitive advantage for the final product. This intension is only achieved when each and every element of the supply chain considers customers’ needs in every function of theirs. This paper studies scheduling in the supply chain of a multi-site manufacturing system. It is assumed that some suppliers produce raw material or initial parts and convey them by a fleet of vehicles to a multi-site manufacturer.

Analyzing the interaction of factors for flexibility in supply chains

Abstract: Purpose In the present scenario of global competition and economic recession, most of the organizations are facing tough challenge to survive in the market because of shortening product life cycle and reducing profit margin. Customers are seeking better design, production and delivery, which have made firms to concentrate on flexibility in supply chains. Therefore, the purpose of this study is to identify major factors and develop a suitable framework for flexibility in supply chains. Design/methodology/approach Based on literature review, about 14 factors have been identified. To develop relationship among these factors, a team of five experts from industry and academia was formed. Based on inputs from experts, different relationships are developed among factors to form structural self-interaction matrix (SSIM). Based on this matrix, a flexibility framework is developed by interpretive structural modelling approach. Findings Top management commitment, strategy development for flexible SC, application of advance technology and IT tools, information sharing in SC members, trust development among supply chain members have emerged as major driving factors. Logistics and warehouse management, suppliers flexibility, distribution flexibility and manufacturing flexibility have emerged as dependent factors. Research limitations/implications Framework developed in this study is based on interpretive structural modelling. This framework can be further validated with some case analysis and empirical findings. Originality/value Findings of the study can be useful for industry professionals to develop strategies for flexible supply chains. It will help them in taking new initiatives for making supply chains more responsive and proactive for customers demand.

A PCA-DEA framework for stock selection in Indian stock market

Abstract: Purpose Portfolio optimization is the process of making an investment decision on a set of assets to realize high returns with low risk. It has three major stages: asset selection, asset weighting and asset management. Asset selection is an important phase because it influences asset allocation and ultimately affects the returns of a portfolio. Today, there is an increase in the number of listings on a stock exchange. Therefore, it is important for an investor to screen and select stocks for investment. This study focuses on the first stage of the portfolio optimization problem, namely, asset selection. The purpose of this study is to evaluate and select profitable stocks quoted on National Stock Exchange (NSE) for portfolio optimization. Design/methodology/approach Financial ratios are considered as the input and output parameters for evaluating the financial performance of the firms. This study adopts a hybrid principal component analysis (PCA) and data envelopment analysis (DEA) approach to evaluate the efficiency of the firms. Based on the efficiency scores, the firms are selected for the investment process. Findings The model helps to determine the relative efficiencies of the firms. The efficient firms are considered to be the potential stocks for investment. It helps the investors to screen the stocks from a large number of stocks quoted on NSE. Research limitations/implications One of the limitations of the standard DEA model is that it fails to discriminate the firms when the number of input and output parameters are larger than the number of firms. To overcome this problem, either a parameter can be ignored or weight-restricted DEA can be applied. When an input/output parameter is dropped, the information in that variable is lost. Weight-restricted DEA model uses expert opinion for measuring the relative importance of input and output parameters. Expert opinion is subjective and might be biased. The PCA-DEA model helps to identify the efficient firms by improving the discriminatory power of standard DEA without any loss of information and without the need for expert opinion, which might be biased. Practical implications Asset selection is an important stage in the investment process. Selection of stocks based on the efficiency score is an easier option available to the investors. But the misclassification of firms either due to biased expert opinion or discrimination inability of DEA can be costly to an investor. The PCA-DEA model overcomes both these limitations. Investors can select the potential candidates for asset allocation based on the efficiency scores obtained using the PCA-DEA model. Further, the relative efficiencies obtained can help the firms to benchmark their performance against the best performing firms within their industry. Originality/value This paper is one of few papers to adopt the PCA-DEA framework to select stocks in the Indian stock market.

3PL evaluation and selection using integrated analytical modeling

Abstract: Purpose The purpose of this paper is to propose a framework for evaluating and selecting the most optimal third-party logistics (3PL) service provider vendor among the available ones. Selection is done based on the performance values of the vendors on certain predefined criteria. Design/methodology/approach An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem has been used to develop a new model for the selection of 3PL vendor. First, DEA is used to evaluate the efficiency of each vendor according to the identified criteria. Second, TOPSIS is applied to rank the maximally efficient vendors. Finally, LP problem is stated and solved to ascertain the quantities to be allocated to each maximally efficient vendor in the context of multiple logistics provider. The proposed DEA–TOPSIS–LP (DETOLP) model is finally tested with real-time industry data for 3PL vendor evaluation and selection. The study, thus, proposes a three-step hierarchical technique for selection of 3PL vendor based on the multiple criteria decision-making approach. Findings The paper focuses on assessing the performance of 26 vendors using a combined approach of DEA, TOPSIS and LP. It is observed that vendor V4 outperforms all the considered vendors, which exactly corroborates with the present scenario within the company. Research limitations/implications Exclusion of qualitative criteria for 3PL vendor selection and the judgment of weights for TOPSIS can be considered as the limitations of the present work. The study has significant practical implications for organizations belonging to any sector or industry. It can help them in evaluating the existing 3PL vendors and selecting the most efficient among them. Originality/value This paper deals with a framework modeled for 3PL vendor selection. It is the first attempt to utilize an integrated approach, i.e. DETOLP model for evaluation and selection of 3PL. For assessment of the model, real data from an Indian company has been taken to analyze the result and compare it with the present scenario within the company.

Embedding risk in closed-loop supply chain network design: Case of a hospital furniture manufacturer

Abstract: Purpose The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies. Design/methodology/approach The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver. Findings The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant. Practical implications Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks. Originality/value By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.

Performance evaluation and prioritization of organizations based on knowledge management and safety management approaches using DEA: A case study

Abstract: Purpose The purpose of this paper is to propose a method for performance assessment of organizations based on integrated approach of knowledge management and safety management using data envelopment analysis, and the proposed model is then applied in the car industry in Isfahan province to be checked. Therefore, deficiencies can be highlighted and possible strategies can be evolved to improve the performance. Design/methodology/approach As data envelopment analysis is a robust mathematical tool, it has been used to evaluate organizational performance. For discovering the organizational performance of knowledge management and safety management by data envelopment analysis (DEA), the first step is to specify proper criteria. To this end, in this method, the indices in both approaches of knowledge management and safety management were identified. Then, inputs and outputs were specified. Knowledge management and safety management were determined as input indices, and customer satisfaction and accident indicators were the output indices. It is noteworthy that each output index was used one time. In the next stage, performance of organizations was assessed based on both determined approaches and via data envelopment analysis. Finally, the organizations were ranked. Findings The suggested method was implemented in the car industry in the Isfahan province. The obtained results disclosed that among 12 decision-making units, 4 units are efficient when customer satisfaction is the output and 5 units are efficient when accidents indices are the output. In ranking with customer satisfaction as the output, Sepahan Atlas Pump Company was ranked first via super efficiency method, data envelopment analysis and similarity to ideal solution. In ranking with accidents as the output, Sepahan Atlas Pump Company ranked first via strong efficiency method and Sanatgar Company ranked first via data envelopment analysis and similarity to ideal solution. Originality/value Knowledge has been recognized as one of the valuable resources, and knowledge management would greatly effect improvement of job quality. Knowledge level increase is led by better performance and less errors. Consequently, it can enhance the organizational health and safety. There are some studies which have been conducted on safety management or knowledge management performance analysis. The organizational performance evaluation based on integrated approach of knowledge management and safety management is an important issue which is less considered in theory and practice. Thus, the authors have proposed a method which is able to evaluate the organization based on this integrated approach with functional indices, which resulted in accurate results, and finally, ranking can show the organization status to determine proper strategies.

Genetic scatter search algorithm to solve the one-commodity pickup and delivery vehicle routing problem

Abstract: Purpose In this paper, the author introduces a new variant of the pickup and delivery transportation problem, where one commodity is collected from many pickup locations to be delivered to many delivery locations within pre-specified time windows (one–to many–to many). The author denotes to this new variant as the 1-commodity pickup-and-delivery vehicle routing problem with soft time windows (1-PDVRPTW). Design/methodology/approach The author proposes a hybrid genetic algorithm and a scatter search to solve the 1-PDVRPTW. It proposes a new constructive heuristic to generate the initial population solution and a scatter search (SS) after the crossover and mutation operators as a local search. The hybrid genetic scatter search replaces two steps in SS with crossover and mutation, respectively. Findings So, the author proposes a greedy local search algorithm as a metaheuristic to solve the 1-PDVRPTW. Then, the author proposes to hybridize the metaheuristic to solve this variant and to make a good comparison with solutions presented in the literature. Originality/value The author considers that this is the first application in one commodity. The solution methodology based on scatter search method combines a set of diverse and high-quality candidate solutions by considering the weights and constraints of each solution.

Analysis of Indian retail demand chain using total interpretive modeling

Abstract: Purpose The study aims to present demand chain management (DCM) modeling of Indian apparel retailers. This will result in a structured model presenting contextual interrelationship among DCM variables so that retailers can proactively manage their demand chain. Design/methodology/approach The research follows an exploratory research design. It initially involves identification and analysis of influential factors of the implementation of DCM practices through the review of literature. Then, these variables were analyzed using total interpretive structural modeling or TISM followed by a statistical verification and case-based validation of the model. Findings The major findings of the paper are: top-management commitment and support, information management and supply chain agility in supply chain are the most significant enablers with the highest driving power. The other apparel retail specific significant variables are assortment planning, category management and marketing orientation. The model also indicates that the firms that implement customer-centric DCM practices do well in terms of organizational performance and thereby achieve differential advantage over their competitors. Research limitations/implications Because the literature on DCM is still in nascent stage, the study bases itself on interpretive method; that is, TISM of analysis with a limited number of experts. Future studies may consider larger sample with more advanced statistical tools such as structural equation modeling for further validation of the findings. Originality/value The novelty of the paper lies in the study of an emerging supply chain philosophy; that is, DCM and its key practices per se. It has rarely been studied from the theory building perspective hitherto. Moreover, TISM-based approach is applied for the first time to study the DCM practices and its drivers vis-a-vis dependents.

An interpretive structural modeling approach to advertisement effectiveness in the Indian mobile phone industry

Abstract: Purpose The mobile phone industry in India is highly competitive, fast paced and technology-driven. In such a hyper competitive era, effective advertising is considered a key success driver for a mobile phone brand. The purpose of this paper is to identify advertisement effectiveness dimensions for Indian mobile phone industry and to develop hierarchical interrelationships among these dimensions in the Indian print context. Design/methodology/approach Structured Delphi approach is used to derive the set of dimensions for advertisement effectiveness. Further, techniques such as interpretive structural modeling and MICMAC analysis are used to establish hierarchical linkages among identified dimensions. Findings On the basis of experts’ opinion, refinement through structured Delphi resulted in the identification of 14 advertisement effectiveness dimensions specific to Indian mobile phone industry. Interpretive structural modeling assisted in the development of linkages among these identified dimensions based on their interrelations. Further, attention, relevance, excitability, liking and consumer preference, etc., turned out to be the dimensions of utmost importance for measuring advertisement effectiveness for the Indian mobile phone industry. Research limitations/implications The present research work is limited to the recognition and development of hierarchical interrelationships among advertisement effectiveness dimensions specific to mobile phone business in the Indian print context only. Further studies may be carried out for other product or service category in some different media context. Practical implications The present research has several significant implications for academics and advertising practitioners involved in designing and developing promotional campaigns for mobile phone brands in India. The identified 14 dimensions and developed hierarchical model provide valuable insights for improving advertisement effectiveness. Originality/value This paper demonstrated successful implementation of Delphi and interpretive structural modeling technique to explore the research area of advertisement effectiveness.

Hybrid scheduling and maintenance problem using artificial neural network based meta-heuristics

Abstract: Purpose The purpose of this paper is to present a new mathematical model for the unrelated parallel machine scheduling problem with aging effects and multi-maintenance activities. Design/methodology/approach The authors assume that each machine may be subject to several maintenance activities over the scheduling horizon and a machine turn into its initial condition after maintenance activity and the aging effects start anew. The objective is to minimize the weighted sum of early/tardy times of jobs and maintenance costs. Findings As this problem is proven to be non-deterministic polynomial-time hard (NP-hard), the authors employed imperialist competitive algorithm (ICA) and genetic algorithm (GA) as solution approaches, and the parameters of the proposed algorithms are calibrated by a novel parameter tuning tool called Artificial Neural Network (ANN). The computational results clarify that GA performs better than ICA in quality of solutions and computational time. Originality/value Predictive maintenance (PM) activities carry out the operations on machines and tools before the breakdown takes place and it helps to prevent failures before they happen.

A multi-objective location-allocation model in mass casualty events response

Abstract: Purpose When designing an optimization model for use in a mass casualty event response, it is common to encounter the heavy and considerable demand of injured patients and inadequate resources and personnel to provide patients with care. The purpose of this study is to create a model that is more practical in the real world. So the concept of “predicting the resource and personnel shortages” has been used in this research. Their model helps to predict the resource and personnel shortages during a mass casualty event. In this paper, to deal with the shortages, some temporary emergency operation centers near the hospitals have been created, and extra patients have been allocated to the operation center nearest to the hospitals with the purpose of improving the performance of the hospitals, reducing congestion in the hospitals and considering the welfare of the applicants. Design/methodology/approach The authors research will focus on where to locate health-care facilities and how to allocate the patients to multiple hospitals to take into view that in some cases of emergency situations, the patients may exceed the resource and personnel capacity of hospitals to provide conventional standards of care. Findings In view of the fact that the problem is high degree of complexity, two multi-objective meta-heuristic algorithms, including non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA), were proposed to solve the model where their performances were compared in terms of four multi-objective metrics including maximum spread index (MSI), spacing (S), number of Pareto solution (NPS) and CPU run-time values. For comparison purpose, paired t-test was used. The results of 15 numerical examples showed that there is no significant difference based on MSI, S and NPS metrics, and NRGA significantly works better than NSGA-II in terms of CPU time, and the technique for the order of preference by similarity to ideal solution results showed that NRGA is a better procedure than NSGA-II. Research limitations/implications The planning horizon and time variable have not been considered in the model, for example, the length of patients’ hospitalization at hospitals. Practical implications Presenting an effective strategy to respond to a mass casualty event (natural and man-made) is the main goal of the authors’ research. Social implications This paper strategy is used in all of the health-care centers, such as hospitals, clinics and emergency centers when dealing with disasters and encountering with the heavy and considerable demands of injured patients and inadequate resources and personnel to provide patients with care. Originality/value This paper attempts to shed light onto the formulation and the solution of a three-objective optimization model. The first part of the objective function attempts to maximize the covered population of injured patients, the second objective minimizes the distance between hospitals and temporary emergency operation centers and the third objective minimizes the distance between the warehouses and temporary centers.

Management practices and modeling the seasonal variation in health care waste: A case study of Uttarakhand, India

Abstract: Purpose Management of hazardous waste is a big challenge to a common biomedical waste treatment facility (CBWTF) because of variations in the amount of different kinds of waste collected and treated from various health-care facilities (HCFs). Hence, prediction of health-care waste (HCW) will be very helpful for the CBWTF in allocation of resources, transportation, storage and disposal of medical waste (MW). This study aims to focus on the current MW handling and disposal practices at CBWTF in Uttarakhand, India. The study also models the seasonal variation in the HCW quantities collected and treated in CBWTF at Uttarakhand (India). Design/methodology/approach Data were collected for two years (2013 and 2014) from CBWTF, and polynomial regression models were used to represent the complex nonlinear relationship among the variables. Findings The fixed trends in the waste generated in two years represent the seasonal variations and illness patterns. The load of approximately 527 kg/day biomedical waste, including all the three categories (red, yellow and blue), was estimated at CBWTF at Uttarakhand, India. The composition of the total waste was calculated as: yellow category (327 kg/day, 62.23 per cent), red category (190 kg/day, 36.66 per cent) and blue category (10 kg/day, 1.44 per cent). CBWTF needs to run an incinerator for 3.30 h, autoclaving machine for 4 h and shredder for 20 min daily as per the calculated load. Research limitations/implications This study is focused on only one CBWTF in Uttarakhand, so the model needs to be validated considering other facilities. Practical implications The model will help the CBWTF to plan its capacity and allocate resources. Social implications Infectious waste coming out from HCFs can be managed in a proper way. Originality/value This study is the first of its kind conducted for CBWTF, Uttarakhand, India.

Energy consumption flow and regional economic development: evidence from 25 economies

Abstract: Purpose This paper aims to figure out the relationship between energy consumption flow from a new perspective of embodied energy inventory index (EEII) and regional economic growth. Design/methodology/approach The input-output approach has been applied to calculate embodied energy inventory (EEI) and EEII using the data of 25 economies. Meanwhile, cluster analysis and panel data modeling were applied to carry out detailed research. Findings The results of cluster analysis show that there is a roughly negative relationship between EEII and gross domestic product (GDP) per capita, although there are some exceptions, such as Russia and Taiwan (Province of China). Panel data model results provide further evidence that there is a negative relationship between EEII and GDP per capita. Population is an important productive factor in the regional economic development. The study showed a positive relationship between EEII and population. Therefore, energy consumption flow is closely related to regional economic development. Originality/value The value of this paper is to use EEI and EEII to comprehensively clarify the energy consumption flow. The advantage of EEII is that it can reflect the energy embodied in fixed assets and infrastructure.

Vendor-managed inventory in the joint replenishment problem of a multi-product single-supplier multiple-retailer supply chain: A teacher-learner-based optimization algorithm

Abstract: Purpose In this paper, the joint replenishment problem is modeled for a two-level supply chain consisting of a single supplier and multiple retailers that use the vendor-managed inventory (VMI) policy for several products. This paper aims to find the optimal number of products to order in both policies, the optimal times at which each retailer orders the products in the traditional policy and the optimal times at which the supplier orders the product in the VMI policy. Design/methodology/approach The problem is first formulated into the framework of a constrained integer nonlinear programming model; then, the problem is solved using a teacher-learner based optimization algorithm. As there are no benchmarks available in the literature, a genetic algorithm is used as well to validate the results obtained. Findings The solutions obtained using both the algorithms for several numerical examples are compared to the ones of a random search procedure for further validation. A real case is solved at the end to demonstrate the applicability of the proposed methodology and to compare both the policies. Research limitations/implications The paper does not have any special limitations. Practical implications The study has significant practical implications for the sellers and for the suppliers who have to get the most profit. Also, satisfying the constraints make decision more complicated. Originality/value This paper has two main originalities. The authors have developed the model of the joint replenishment problem and have contributed in the problem-solving process. They have used a new meta-heuristic and then compared it to a classic one.

Employing fuzzy ANP for ranking the personality of international brands in the sports shoe industry

Abstract: Purpose This paper aims to provide a quantitative basis to analytically determine the ranking of the brand personality of Adidas, Asics, Nike, Puma and Saucony brands among Iranian customers via a conventional multi-criteria decision-making (MCDM) method. Design/methodology/approach Data for determining the importance of evaluation criteria and ranking of brands are gathered by means of distributing questionnaires among a group of Iranian customers of sport shoes, as well as some industrial experts. The fuzzy analytic network process (FANP) was used to rank the brands with regard to dependencies between criteria and alternatives. Findings The results indicate that FANP is a capable method which provides invaluable insights for strategic marketing decisions in the sport product industry. Results show Adidas has the best performance in the sports shoe market compared to the other four brands. In this study, it was found that expertise sophistication was the most important criterion among Aaker’s five main criteria. Originality/value The value of this paper is applying FANP decision-making method for ranking sport shoe brands. This method has not been commonly used in the area of marketing, hence it is added to the pool of techniques used in ranking brands. In addition, evaluation and ranking of brands can be very useful for both academic research and practice. Researchers can benchmark the competences of each brand through evaluating them, and industrialists can extract the competitive advantages of the selected brands.

A multiproduct economic order quantity model with simulated annealing application

Abstract: Purpose This paper aims to present a set of five models for the economic order quantity problem. Four models solve problems for a single product: incremental discounts with or without backorders and all-unit discounts with or without backorders, and the last model solves problems for the multiproduct case. Design/methodology/approach A basic integer non-linear model with binary variables is presented, and its flexible structure allows for all five models to be utilised with minor modifications for adaptation to individual situations. The multiproduct model takes into consideration the work of Chopra and Meindl (2012), who studied two types of product aggregations: full and adaptive. To find optimal or near-optimal solutions for the multiproduct case, the authors propose a simulated annealing metaheuristic application. Numerical examples are presented to improve the comprehension of each model, and the authors also present the efficiency of the simulated annealing algorithm through an example that aggregates 50 products, each one with different discount schemes and some allowing backorders. Findings Our model proved to be efficient at finding optimal or near optimal solutions even when confronted with mathematical complexities such as the allowance of backorders and incremental discounts. Originality/value Finally our model can process a mix of products with different discount schemes at the same time, and the simulated annealing metaheuristics could find optimal or near optimal solutions with very few iterations.

Rise in level of trust and trustworthiness with trust building measures: A mathematical model

Abstract: Purpose The aim of this paper is to develop a model for presenting level of trust and analyzing the contribution of various trust-building measures undertaken by an organization. Design/methodology/approach The conceptual framework for the model is based on previous research and the concept of trust and its implications in business environment. This model includes various stages of trust measured against time and trust building measures (TBM). This trust model relates the trustee’s position with the trustor at any point in time and describes its impact on trustee’s position in terms of trustworthiness (sum of “trust deficit” and “trust gain”). 10;Vectors and linear Algebra equations are used to construct the model supplemented with an example from real-life business environment for better understanding of the model. 10. Findings A trust framework, elaborating level of trust between two parties is explained with the help of a mathematical model. The model includes various stages of trust measured against time and TBM. Research limitations/implications In the practical application of the model, the authors adopted an existing scale to measure trust levels, which can have its limitations and shortcomings. It is however suggested to choose as specific scale for the industry as possible. Practical implications The model can be applied in any situation, person or environment specially to determine the current situation of organizational trust in business which can be helpful in making decisions. Originality/value The concept of making trust a part of strategy and a tool for decision-making is novel and applicable in all sectors and situations. By providing a real-time view of the level of trust and impact of TBM will help predict future levels of trust and make it an essential part of decision-making process.

Double moderated mediation models: problems and (part) remedies

Abstract: Purpose Researchers in management regularly face modelling issues that involve double-moderated mediation models. Here, the author illustrates how to conceptualise, specify and empirically estimate mediation effects when having to simultaneously account for continuous (Likert type) and nominal (i.e. group) moderator variables. Researchers’ estimates of the mediation effects suffer serious bias because of the effects of unaccounted confounders. This is an issue that plagues management research, and this study aims to show how to address these valid reservations for its focus models. In aiming to inform a wider management audience, the study deliberately uses the rich context of a focus case as this allows the author to clarify the nuances that management researchers face applying double-moderated mediation models. Specifically, the study’s focus case is on professionals’ willingness to implement a new government policy. The study also combines traditional and Bayesian statistical approaches and explains the differences in estimation and interpretation that are associated with the Bayesian approach. Explaining, and exemplifying the use of, the models, the author focuses on how one can substantially increase the robustness of the methods used in management research and can considerably improve the quality of the generated theoretical insights. The study also clarifies important assumptions and solutions. Design/methodology/approach The study uses a doubled moderated mediation Bayesian approach, and draws the sample data from a population of 5,199 professionals, all members of either the Dutch Association of Psychologists or the Dutch Association for Psychiatry. The data collection process resulted in 1,307 questionnaires being returned, a response rate of 25 per cent. All the items were measured using a Likert scale, ranging from “strongly disagree” to “strongly agree”, unless stated otherwise. Findings Explaining, and exemplifying the use of, the models the study focuses on how one can substantially increase the robustness of the methods used in management research and can considerably improve the quality of the generated theoretical insights. Originality/value This is an original approach exemplified for wider use by management researchers.

Price protection policies with demand uncertainty and strategic consumers

Abstract: Purpose This paper aims to study a retailer’s decision on the price and inventory when facing strategic consumer behavior and demand uncertainty. Price protection is a kind of rebate that the retailer provides to consumers when the price drops during the selling season. The research investigates whether price protection can bring the retailer advantages. This paper compares price protection’s impact with price commitment. In addition, the paper studies the price protection’s impacts on supplier of the supply chain. Design/methodology/approach In this model, there are three alternative strategies for retailer: no price protection policy, full price protection policy and partial price protection policy. The selling season is divided into two periods: regular period and sale period. In the regular period, the products are sold at a regular price. In the sale one, the products are sold at a lower price. By adopting rational expectations equilibrium, this paper analyzes retailer’s optimal price and order quantity under each policy and compares optimal decisions and maximum profits of three policies. Findings This paper finds that the price protection has a positive influence on the retailer. Strategic consumers are induced to purchase at the regular period. It can simultaneously increase retailer’s profit and reduce inventory risk. Meantime, full price protection is chosen as the optimal policy. By comparing full price protection’s impacts with price commitment, full price protection is considered as the most profitable strategy, while price commitment can bring lower inventory risk. In addition, the profit of supplier would decrease because of price protection. Originality/value This research provides a new method to address the negative effects of strategic consumer behavior. It also brings some managerial insights to some retailers, especially online ones, on whether to adopt price protection.

Causal modelling of HR flexibility and firm performance in Indian IT industries

Abstract: Purpose This paper aims to measure the human resource (HR) flexibility and firm performances confirmatory model and to map the causal relation structures in the HR flexibility and firm performance dimensions using the DEMATEL method. Design/methodology/approach Data were collected from leading national and multinational information technology (IT) firms operating in the southern part of India. Confirmatory factor analysis was used to measure the confirmatory model, and the DEMATEL method was used to map the causal relation among the dimensions of HR flexibility and firm performance. Findings HR flexibility could exist across IT firms. Organisations are required to anticipate and respond promptly to changing conditions in such a way that both technical and stakeholders’ complexity are effectively managed. Research limitations/implications The study was conducted at leading national and multinational IT firms operating in the southern part of India. Practical implications HR flexibility allows employees with a wide variety of work styles and lifestyles to be successful contributors, to advance and to lead in the parent firm. It brings out diversity and individuality, shared responsibility, wholeness, etc., among the employees. It applies to work schedules and career paths across the organisation. IT firms are advised to adopt an external focus, an organic and employee-oriented approach and long-term orientation. Originality/value Confirming the measurement model and mapping the causal relationship among the dimensions of HR flexibility and firm performance would be the novel contributions to the research in the areas of HR flexibility and firm performance with regard to IT firms. This paper contributes to the literature by theoretically and empirically investigating such relationships, thereby addressing the research gaps reviewed from literature.