• A flexible multicriteria decision-making-taliem-ir

    A flexible multicriteria decision-making methodology to support the strategic management of Science, Technology and Innovation research funding programs

    تومان

    Research funding programs are a policy instrument utilized by governments to influence the innovation process. They are usually elaborated, launched and managed by research funding agencies. In order to select the most adequate research projects, agencies often rely on the peer review process. This paper introduces a methodology to support funding decisions based on the peer review process. The methodology involves the use of a multicriteria decision model to support the assessment, evaluation, prioritization and selection of applications, under a multi-step decision-making process, which fits into a strategic management cycle within the agency. The Multiattribute Value Theory, being considered under a Value Focused Thinking approach, provides a basis for the construction of the multicriteria decision model. The good practices in peer review and also a logical framework for program management are considered by the methodology. A pilot study, presented in the paper, involved a retrospective implementation of a peer review process in the context of a program launched by the Ministry for Science, Technology, Innovations and Communications and the National Council of Technological and Scientific Development, in Brazil. The methodology allowed a clear distinction of roles. The agency staff in the role of decision-makers was responsible for making value judgments on behalf of the agency. The experts, in the role of committee members and ad hoc reviewers, contributed with their expertise by providing objective assessments. Such assessments served as a basis for evaluating the applications, characterizing the possible portfolios, and can be considered as data in future program evaluation studies.

     

  • A Fuzzy TOPSIS Method for Performance.taliem-ir

    A Fuzzy TOPSIS Method for Performance Evaluation of Reverse Logistics in Social Commerce Platforms

    تومان

    Reverse logistics initiatives with social commerce not only provide opportunities for firms to create new sources of revenue but also demonstrate their corporate social responsibility via social, green, and environmental activities. Thus, a growing number of companies are attempting to streamline their social commerce platforms to effectively handle reverse logistics. The purpose of this study is to identify the criteria that should be used in designing and
    evaluating social commerce based reverse logistics processes by firms. We tested the effectiveness of the identified criteria by using them to evaluate the reverse logistics practices of three major global firms that use social commerce platforms. First, we identified the criteria from a thorough review of the literature. Then, we invited five experts to provide (linguistic) ratings of these firms on the selected criteria, using a fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique with FLINTSTONES (a software tool) to
    generate aggregate scores for the assessment and evaluation of reverse logistics practices in social commerce platforms. Sensitivity analysis was also provided to monitor the robustness of the approach. The results of the study identified that four dominant criteria (reverse logistics performance indicators) in the social commerce platform: Customer relationship, Usage risk, Reviews, and Quality control.

     

  • A review of approaches to uncertainty assessmen-taliem-ir

    A review of approaches to uncertainty assessment in energy system optimization models

    تومان

    Energy system optimization models (ESOMs) have been used extensively in providing insights to decision makers on issues related to climate and energy policy. However, there is a concern that the uncertainties inherent in the model structures and input parameters are at best underplayed and at worst ignored. Compared to other types of energy models, ESOMs tend to use scenarios to handle uncertainties or treat them as a marginal issue. Without adequately addressing uncertainties, the model insights may be limited, lack robustness, and may mislead decision makers. This paper provides an in-depth review of systematic techniques that address uncertainties for ESOMs. We have identified four prevailing uncertainty approaches that have been applied to ESOM type models: Monte Carlo analysis, stochastic programming, robust optimization, and modelling to generate alternatives. For each method, we review the principles, techniques, and how they are utilized to improve the robustness of the model results to  provide extra policy insights. In the end, we provide a critical appraisal on the use of these methods.

     

  • Analysing disposition strategies -taliem-ir

    Analysing disposition strategies in reverse supply chains: Fuzzy TOPSIS approach

    تومان

    Purpose – The article aims to explore the product disposition strategies in reverse supply chains and to develop a framework to prioritize these strategies for effective reverse supply chain implementation. Design/Methodology/Approach –The disposition strategies, based on the literature review were selected, and fuzzy TOPSIS methodology has been applied for the prioritization of these disposition strategies. A case of cell phone  manufacturing firm is discussed for the illiustration and validation of the methodology. Three respondants from the firm helped in exploring the disposition strategies and data collection of the firm. Findings – The results of the study show that dissemble and recycle is the most preferred disposition strategy for the firm. Redistribution of returned products after their refurbishing is second most prioritized disposition strategy. Landfill and inciretion of cell phones is the last and least prefreferred option for the firm. Research limitations/implications- The study will  provide useful guidance to the firm fordisposition decision making of cell phones returned to the firm. It will help academicians and practitioners for evaluating, improving and benchmarking the disposition strategies for the disposition of returned cell phones. One of the limitations of the study is that it only considers the single case of   manufacturing firm. In future, more case studies may be carried out for generalization of the results.Originality / value – It is evident from the literature review that there are very few studies on disposition decisions in reverse supply chain. Also, disposition strategies for cell phones are first time being explored and prioritized.Hence, this study can be viewed as an attempt to increase the level of awareness on reverse supply chain issues.

     

  • Application of Analytic Hierarchy Process-taliem-ir

    Application of Analytic Hierarchy Process in Network Level Pavement Maintenance Decision-making

    تومان

    This paper proposes an Analytic Hierarchical Process (AHP) theory based method to determine the weight of the decision-making influence factors, considering their relative significance and generating an overall ranking for each road section. A case study on the highway network maintenance priority was conducted to illustrate the proposed procedure. A total of five pavement maintenance decision-making related factors were considered in the study, including pavement performance, pavement structure strength, traffic loads, pavement age and road grade. The weightings of the five factors were quantified through AHP method. Then, the comprehensive ranking index value Ui was determined, which indicated the maintenance priority of a road section in network level decision-making. From the aspect of maintenance cost, the sensitivity analysis results were in accordance with the weightings of different maintenance decision-making factors. The pavement maintenance cost was significantly sensitive to the change of pavement performance. The case study clearly demonstrated the applicability and rationality of the AHP .theory based decision-making method and it can be used as a guideline for pavement maintenance agencies

     

  • Big data analytics architecture design-taliem-ir

    Big data analytics architecture design—an application in manufacturing systems

    تومان

    Context: The rapid prevalence and potential impact of big data analytics platforms have sparked an interest amongst different practitioners and academia. Manufacturing organisations are particularly well suited to benefit from data analytics platforms in their entire product lifecycle management for intelligent information processing, performing manufacturing activities, and creating value chains. This requires re-architecting their manufacturing  legacy information systems to get integrated with contemporary data analytics platforms. A systematic re-architecting approach is required incorporating careful and thorough evaluation of goals for data analytics  doption. Furthermore, ameliorating the uncertainty of the impact the new big data architecture on system quality goals is needed to avoid cost blowout in implementation and testing phases. Objective: We propose an approach to reason  about goals, obstacles, and to select suitable big data solution architecture that satisfy quality goal preferences and constraints of stakeholders at the presence of the decision outcome uncertainty. The approach  will highlight situations that may impede the goals. They will be assessed and resolved to generate complete requirements of an architectural solution. Method: The approach employs goal-oriented modelling to identify obstacles causing quality goal failure and their corresponding resolution tactics. It combines fuzzy logic to explore uncertainties in solution architectures and to find an optimal set of architectural decisions for the big data enablement process of manufacturing systems. Result: The approach brings two innovations to the state of the art  of big data analytics platform adoption in manufacturing systems: (i) A systematic goal-oriented modelling for exploring goals and obstacles in integrating manufacturing systems with data analytics platforms at the requirement level and (ii) A systematic analysis of the architectural decisions under uncertainty incorporating stakeholders’ preferences. The efficacy of the approach is illustrated with a scenario of reengineering a hyper-connected manufacturing collaboration system to a new big data architecture.

     

  • Biomass logistics A review of important-taliem-ir

    Biomass logistics: A review of important features, optimization modeling and the new trends

    تومان

    Biomass logistics comprise of inter-dependent operations related to harvesting and collection, storage, preprocessing, and transportation. Its high cost represents one of the barriers in widespread use of biomass for energy and fuel production. Therefore, improving and optimizing biomass logistics are essential in overcoming this barrier. Biomass logistics was reviewed in a previous study that aimed at categorizing logistics operations, but the inherent issues and complexities, and how they were incorporated in mathematical models were not discussed in detail. The objective of this paper is to review the important features of biomass logistics operations, discuss how they were incorporated in mathematical optimization models, and explain the new trends in biomass logistics optimization. Differences between the models dealing with forest-based and agriculture-based biomass are highlighted. Important features incorporated in logistics models include demand-driven and supplydriven collection, collection of biomass in different forms, storage at intermediate facilities, biomass quality deterioration, inter-modal distribution for long-distance transportation, operational level transportation planning, and planning the pre-processing of biomass. Recent trends in biomass logistics models include the consideration of scattered availability of biomass across supply areas, uncertainties in biomass supply, integration with GIS, emissions from logistics operations, and traffic congestion due to biomass transportation. Most of the literature on biomass logistics focused on medium-term planning, while that for short-term planning is still in its infancy. The current biomass logistics models focused mainly on economic objectives, while environmental concerns related to emissions from logistics activities received limited attention. The trade-off between environmental and economic aspects of biomass logistics operations have not been investigated. Social aspects such as increase in traffic congestion due to biomass transportation received limited attention in the literature. Most of the previous models were tested on hypothetical cases, while developing suitable models to address practical issues in real case studies would be valuable.

     

  • Blockchain’s roles in meeting key-taliem-ir

    Blockchain’s roles in meeting key supply chain management objectives

    تومان

    Arrival of blockchain is set to transform supply chain activities. Scholars have barely begun to systematically assess the effects of blockchain on various organizational activities. This paper examines how blockchain is likely to affect key supply chain management objectives such as cost, quality, speed, dependability, risk reduction, sustainability and flexibility. We present early evidence linking the use of blockchain in supply chain activities to increase transparency and accountability. Case studies of blockchain projects at various phases of development for diverse purposes are discussed. This study illustrates the various mechanisms by which blockchain help achieve the above supply chain objectives. Special emphasis has been placed on the roles of the incorporation of the IoT in blockchain-based solutions and the degree of deployment of blockchain to validate individualsand assetsidentities.

     

  • Clicks versus Bricks the role of durability-taliem-ir

    Clicks versus Bricks: the role of durability in marketing channel strategy of durable goods manufacturers

    تومان

    We develop a two-period dual-channel model for a durable goods manufacturer to investigate how product durability and the channel structure create strategic issues that are significantly different from those in managing a dual channel for nondurables. The manufacturer can sell directly by its own e-channel and indirectly via an independent reseller. Our game-theoretic model nests Arya et al. (2007) [Arya et al., 2007. The bright side of supplier encroachment. Marketing Science 26 (5): 651-659.] as a special case when product durability reduces to zero and thus generalizes it to the durable goods setting. The equilibrium solutions indicate that, when the product is durable, both parties’ profitability strongly depends on product durability and direct selling cost. In particular, we find that, compared to encroaching the reseller’s market by direct selling online, it is optimal for the  manufacturer to open an inactive e-channel that serves only as an information medium. Moreover, we find that,  contrary to Arya etal.’s (2007) results, if product durability is moderate, for any direct selling cost, manufacturer’s encroachment is always detrimental to the reseller, and thus its bright side disappears. We test our model’s  theoretical predictions of the effectsof product durability on manufacturer’s and reseller’s profitability with data from the U.S. x86 computer server market, and find strong empirical supportprofitability of both parties is higher when product durability is sufficiently low or sufficiently high, and lower when durability is intermediate.

     

  • Do health information technology investments-taliem-ir

    Do health information technology investments impact hospital financial performance and productivity?

    تومان

    In this study, we examine the associations between health information technology expenses, intermediate business processes, hospital financial performance and productivity. Research using hospital financial data prior to the Health Information Technology for Economic and Clinical Health Act is limited. Using Definitive Healthcare data, we find that health information technology expenses, including information technology operating expense and capital expense, are positively associated with hospitals’ return on assets and productivity. In addition, investments also generate effects via hospital’s intermediate business processes, such as electronic health records (EHR) adoption, and quality measures. Our findings suggest that hospitals’ health information technology investments involving intermediate business  processes are associated withpositive financial performance and productivity following the implementation of the Health Information Technology for Economic and Clinical Health Act.

     

  • Efficiency evaluation based on data envelopment-taliem-ir

    Efficiency evaluation based on data envelopment analysis in the big data context

    تومان

    Data envelopment analysis (DEA) is a self-evaluation method which assesses the relative efficiency of a particular decision making unit (DMU) within a group of DMUs. It has been widely applied in real-world scenarios, and traditional DEA models with a limited number of variables and linear constraints can be computed easily. However, DEA using big data involves huge numbers of DMUs, which may increase the computational load to beyond what is practical with traditional DEA methods. In this paper, we propose novel algorithms to accelerate the computation process in the big data environment. Specifically, we firstly use an algorithm to divide the large scale DMUs into small scale and identify all strongly efficient DMUs. If the strongly efficient DMU set is not too large, we can use the efficient DMUs as a sample set to evaluate the efficiency of inefficient DMUs. Otherwise, we can identify two reference points as the sample in the situation of just one input and one output. Furthermore, a variant of the algorithm is presented to handle cases with multiple inputs or multiple outputs, in which some of the strongly efficient DMUs are reselected as a reduced-size sample set to precisely measure the efficiency of inefficient DMUs. Last, we test the proposed methods on simulated data in various scenarios.

     

  • Efficiency evaluation based-taliem-ir

    Efficiency evaluation based on data envelopment analysis in the big data context

    تومان

    Data envelopment analysis (DEA) is a self-evaluation method which assesses the relative efficiency of a particular decision making unit (DMU) within a group of DMUs. It has been widely applied in real-world scenarios, and traditional DEA models with a limited number of variables and linear constraints can be computed easily. However, DEA using big data involves huge numbers of DMUs, which may increase the computational load to beyond what is practical with traditional DEA methods. In this paper, we propose novel algorithms to accelerate the computation process in the big data environment. Specifically, we firstly use an algorithm to divide the large scale DMUs into small scale and identify all strongly efficient DMUs. If the strongly efficient DMU set is not too large, we can use the efficient DMUs as a sample set to evaluate the efficiency of inefficient DMUs. Otherwise, we can identify two reference points as the sample in the situation of just one input and one output. Furthermore, a variant of the algorithm is presented to handle cases with multiple inputs or multiple outputs, in which some of the strongly efficient DMUs are reselected as  a reduced-size sample set to precisely measure the efficiency of inefficient DMUs. Last, we test the proposed methods on simulated data in various scenarios.

  • Exploration of Social Sustainability-taliem-ir

    Exploration of Social Sustainability in Healthcare Supply Chain

    تومان

    Social sustainability is concerned with the human side of sustainability. The literature indicates a growing movement towards adopting social practices in the supply chain, and despite the diffusion of the topic, it appears that social sustainability is relatively new in the  service sector in general and in the healthcare sector in particular. This study explored this issue and identified the motivators, barriers, and enablers of social sustainability in a healthcare supply chain with the lens of “stakeholder theory” and a focus on four stakeholder groups: suppliers, employees, patients/community and owners/government. These aspects were further explored using a structured research method and specific research objectives. The SIPOC chart was used to list the healthcare suppliers, the inputs (such as   mployees) supplied and used by main processes inhealthcare, the outputs (products and services) of these processes, and their customers (patients and community). This facilitates linkages of different supply chain stakeholders. This is exploratory research; data were collected from various departments of 10 hospitals of United Arab Emirates (UAE), and a comprehensive depiction of what drives,  inhibits, and facilitates social sustainability practices in healthcare as perceived by all stakeholders’ groups was formulated. Study results confirmed that, while separate attention to each stakeholder group is important, a comprehensive analysis of all stakeholders’ perceptions of what constitutes a socially sustainable supply chain would offer more benefits and help hospital managers balance the expectations of  all involved parties.

     

  • Exploring the impact of innovation implementation-taliem-ir

    Exploring the impact of innovation implementation on supply chain configuration

    تومان

    Considering the foreseen digital transformation and rapid dissemination of technological innovations, this paper investigates what happens along the supply chain (SC) when process and product innovation practices are implemented. The research examines the SC strategy and configuration of four product families; it considers the configuration to incorporate the whole range of SC functions and relationships. The paper addresses the little attention paid to the process innovation dimension in SC literature, and develops a framework capturing the dynamics between innovation implementation and configuration decisions and settings. The provided analyses .guide practitioners on better management of innovation implementation along the supply chain

     

  • Stochastic vehicle routing problem-taliem-ir

    Faster rollout search for the vehicle routing problem with stochastic demands and restocking

    تومان

    Rollout algorithms lead to effective heuristics for the single vehicle routing problem with stochastic demands (VRPSD), a prototypical model of logistics under uncertainty. However, they can be computationally intensive. To reduce their run time, we introduce a novel approach to approximate the expected cost of a route when executing any rollout algorithm for VRPSD with restocking. With a sufficiently large number of customers its theoretical speed-up factor is of big-o order 1/3. On a set of instances from the literature, our proposed technique applied to a known rollout algorithm and three variants thereof achieves speed-up factors that range from 0.26 to 0.34 when there are more than fifty customers, degrading only marginally the quality of the resulting routes. Our method also applies to the a priori case, in which case it is exact.