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1 |
Integrating corporate website information into qualitative assessment for benchmarking green supply chain management practices for the chemical industry
ادغام اطلاعات وب سایت شرکت ها در ارزیابی کیفی برای محک زدن شیوه های مدیریت زنجیره تامین سبز برای صنایع شیمیایی-2021 The China’s chemical industry has been endeavoring to promote sustainable development through practicing green supply chain management (GSCM). This paper proposes a multi-criteria decision framework with twenty practices to guide companies in the industry to enact GSCM effectively. The exploratory factor analysis (EFA) has been used to cluster the proposed practices. We found five aspects, including economic initiatives, environmental management, eco-design, resource recycling, and stakeholder and employee, constitute the underlying structure of GSCM. A mixed decision tool combining the entropy weight method (EWM) and the analytic hierarchy process (AHP) has been developed and applied to identify key factors. Official website information has been collected and used to analyse the website contents of five benchmarking companies in the China’s chemical industry. The results reveal that the aspects of environmental management, eco-design and resource recycling are the most important GSCM themes. Moreover, the top five practices are top management support, performing life cycle assessment, managing environmental risks, advancing recycling technologies and integrating reverse logistics. Conceptual and practical implications are discussed. Keywords: Environmental management | Eco-design | Resource recycling | Entropy weight | Analytic hierarchy process | Decision analysis |
مقاله انگلیسی |
2 |
Customer-centric prioritization of process improvement projects
اولویت بندی مشتری محور پروژه های بهبود فرآیند-2020 Today, customers can conveniently compare products and decide how to interact with companies. With customer
centricity becoming an important success factor, companies must drive customer satisfaction not only
through excellent products but also through customer-centric processes. As many companies face an abundance
of action possibilities, fast-changing customer needs, and scarce resources, guidance regarding the customercentric
prioritization of process improvement projects is in high need. As existing approaches predominantly
focus on process efficiency, we propose a decision model that accounts for the effects of process improvement on
customer centricity in line with justificatory knowledge on value-based process decision-making, project portfolio
selection, and the measurement of customer satisfaction. When building the decision model, we adopted
the design science paradigm and used multi-criteria decision analysis as well as normative analytical modeling as
research methods. We evaluated the model by discussing it with practitioners, by building a software prototype,
and by applying it at a German insurance company. Overall, our research extends the prescriptive knowledge on
process prioritization and customer process management. Keywords: Business process management | Business process improvement | Process decision-making | Customer centricity | Project portfolio selection | Kano model |
مقاله انگلیسی |
3 |
A new approach for identifying the Kemeny median ranking
یک روش جدید برای شناسایی رتبه بندی متوسط Kemeny-2020 Condorcet consistent rules were originally developed for preference aggregation in the theory of social choice. Nowadays these rules are applied in a variety of fields such as discrete multi-criteria analysis, defence and security decision support, composite indicators, machine learning, artificial intelligence, queries in databases or internet multiple search engines and theoretical computer science. The cycle issue, known also as Condorcets paradox, is the most serious problem inherent in this type of rules. Solutions for dealing with the cycle issue properly already exist in the literature; the most important one being the identification of the median ranking, often called the Kemeny ranking. Unfortunately its identification is a NP-hard problem. This article has three main objectives: (1) to clarify that the Kemeny median order has to be framed in the context of Condorcet consistent rules; this is important since in the current practice sometimes even the Borda count is used as a proxy for the Kemeny ranking. (2) To present a new exact algorithm, this identifies the Kemeny median ranking by providing a searching time guarantee. (3) To present a new heuristic algorithm identifying the Kemeny median ranking with an optimal trade-off between convergence and approximation . Keywords : Decision analysis | Combinatorial optimisation | Social choice| Multiple criteria | Artificial intelligence| Defence and security| Big data |
مقاله انگلیسی |
4 |
Purchase intention and purchase behavior online: A cross-cultural approach
قصد خرید و خرید آنلاین: رویکردی بین فرهنگی-2020 This article aims to explore the key factors on e-commerce adoption from elements of social psychology, such as attitude, subjective norms, perceived behavioral control, ease of use and perceived usefulness, introducing the study of non-traditional elements like buying impulse, compatibility, and self-efficacy in online stores, contrasting relationships in a cross-cultural environment. The proposed model is tested from quantitative research with a sample of 584 online consumers in Colombia and Spain. The following statistical analyses were conducted: CFA, structural equations, measurement instrument invariance, and multi-group analysis with EQS 6.3 software. The study reveals that self-efficacy in online stores is a key factor in adopting electronic commerce above the cultures studied. Also, there is significant evidence that proves the moderating effect of national culture on several relationships of the model proposed. Results highlight the importance of national culture to understand impulsive buying behavior. The article presents several considerations toward the main elements to generate online purchase intention among consumers in an emerging country and finds substantial differences with consumers in a developed country. Practical implications are made for companies to adopt online channels and expand internationally. Keywords: Online purchase intention | Purchase behavior | Cross-cultural study | Colombia | Spain | Technology management | Technology adoption | Marketing | Consumer attitude | Decision analysis | Business |
مقاله انگلیسی |
5 |
Customer-centric prioritization of process improvement projects
اولویت بندی مشتری محوری پروژه های بهبود فرآیند-2020 Today, customers can conveniently compare products and decide how to interact with companies. With cus- tomer centricity becoming an important success factor, companies must drive customer satisfaction not only through excellent products but also through customer-centric processes. As many companies face an abundance of action possibilities, fast-changing customer needs, and scarce resources, guidance regarding the customer- centric prioritization of process improvement projects is in high need. As existing approaches predominantly focus on process efficiency, we propose a decision model that accounts for the effects of process improvement on customer centricity in line with justificatory knowledge on value-based process decision-making, project port- folio selection, and the measurement of customer satisfaction. When building the decision model, we adopted the design science paradigm and used multi-criteria decision analysis as well as normative analytical modeling as research methods. We evaluated the model by discussing it with practitioners, by building a software prototype, and by applying it at a German insurance company. Overall, our research extends the prescriptive knowledge on process prioritization and customer process management. Keywords: Business process management | Business process improvement | Process decision-making | Customer centricity | Project portfolio selection | Kano model |
مقاله انگلیسی |
6 |
Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis
تولید ذرت و هزینه های زیست محیطی: ارزیابی منابع و برنامه ریزی استراتژیک کاربری اراضی برای امنیت غذایی در شمال غنا با استفاده از تجزیه و تحلیل آمیخته و پوشش داده ها-2020 This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data
Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis
(VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis
(MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern
Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The
business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was
characterised by an external input ≤12 kg/ha/yr inorganic fertilizer with/without the addition of manure in
rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20,
50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows:
(1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input
systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource
use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to
calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b)
benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential
electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was
derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC
approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are
included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal
yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and
Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services)
were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental
performance of the scenarios are compared to maize production systems in other developing regions in order to
put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and
sustainability of agricultural production systems at farm and regional scales, as well as in connecting the
management planning level and regional development considerations. Keywords: Food security | Sustainable agriculture | Strategic land use planning | Emergy-Data envelopment analysis | Environment-biomass-food-energy nexus | Sub-Saharan Africa |
مقاله انگلیسی |
7 |
The application of multi-criteria decision analysis methods into talent identification process: A social psychological perspective
استفاده از روشهای تصمیم گیری چند معیار در فرآیند شناسایی استعداد: چشم انداز روانشناختی اجتماعی-2020 This case study offers a new insight into application of multiple-criteria decision-making methods (MCDM) to
social identity issues in the context of talent management. This study used MCDM to help a high-tech company to
identify potential talents in its sale and marketing team (n=54). MCDM adjusted subjective information consisted
of intangible organisational political issues into a transparent, objective benchmark. The transparency and
consistency of this evaluation process reduced potential social identity disruption between individuals or groups.
Furthermore, the involvement of multiple decision-makers (both managers and employees) in the talent identification
procedure enhanced employees motivation for further development. Keywords: Talent management | Multi-criteria decision making | AHP | Flowsort | GAIA | Visual management |
مقاله انگلیسی |
8 |
Multi-criteria decision-making considering risk and uncertainty in physical asset management
تصمیم گیری چند معیار با توجه به ریسک و عدم اطمینان در مدیریت دارایی های فیزیکی-2020 In this work we present a method for risk-informed decision-making in the physical asset management context
whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses
quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit
analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a
unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off
decisions can be made between risk treatment options. The methodology uses quantitative risk measures for
loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As
Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk
treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified,
and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used
to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization
criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the
Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved
decision-making is illustrated using a numerical example. Keywords: Risk analysis | Uncertainty | Asset management | Multi-criteria decision analysis | Risk matrix | Cost-benefit analysis |
مقاله انگلیسی |
9 |
Sustainability-informed multi-criteria decision support framework for ranking and prioritization of pavement sections
چارچوب پشتیبانی تصمیم گیری چند معیار با آگاهی از پایداری برای رتبه بندی و اولویت بندی بخش های روسازی-2020 Ranking and prioritizing pavement infrastructure for maintenance and rehabilitation have become major
undertakings for several departments of transportation around the globe. This is a complex decisionmaking
problem because multiple and conflicting criteria can contribute to the assessment. Multicriteria
decision analysis (MCDA) techniques evaluate the trade-off between several quantitative and
qualitative criteria and facilitate complex decision-making. This research introduces a framework based
on MCDA to support pavement management decision making, while quantifying emerging
sustainability-related factors such as safety, noise, and pollution in the decision-making process. The
framework features include 1) identifying pavement management main decision elements: objectives,
criteria, and attributes by detailing the problem with a five-level hierarchy structure; 2) employing
combined analytic hierarchy process and multi-attribute utility theory to develop representative set of
utility functions; and 3) ranking and prioritizing large networks of pavement sections while incorporating
sustainability-related criteria. Data used to assess the decision criteria and develop the utility
functions is extracted by means of a questionnaire survey completed by professionals working in the
field of pavement management. The proposed method is applied to a case study consisting of ten
pavement sections extracted from the long-term pavement performance database, wherein the sections
are ranked based on their attributes. Sensitivity analysis is performed to evaluate the impact of the
different criteria on the ranking process. The proposed method has shown potential in ranking pavement
networks based on the identified criteria. Future work can test the performance of the proposed
methodology with a full-scale pavement network and apply it to other civil infrastructure assets to
evaluate its performance with different types of projects. Keywords: Pavement | Management | Multi-criteria | Sustainability | Ranking | Prioritizing |
مقاله انگلیسی |
10 |
Decision analysis and reinforcement learning in surgical decision-making
تجزیه و تحلیل تصمیم گیری و یادگیری تقویت در تصمیم گیری جراحی-2020 Background: Surgical patients incur preventable harm from cognitive and judgment errors made under
time constraints and uncertainty regarding patients’ diagnoses and predicted response to treatment.
Decision analysis and techniques of reinforcement learning theoretically can mitigate these challenges
but are poorly understood and rarely used clinically. This review seeks to promote an understanding of
decision analysis and reinforcement learning by describing their use in the context of surgical decisionmaking.
Methods: Cochrane, EMBASE, and PubMed databases were searched from their inception to June 2019.
Included were 41 articles about cognitive and diagnostic errors, decision-making, decision analysis, and
machine-learning. The articles were assimilated into relevant categories according to Preferred Reporting
Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.
Results: Requirements for time-consuming manual data entry and crude representations of individual
patients and clinical context compromise many traditional decision-support tools. Decision analysis
methods for calculating probability thresholds can inform population-based recommendations that
jointly consider risks, benefits, costs, and patient values but lack precision for individual patient-centered
decisions. Reinforcement learning, a machine-learning method that mimics human learning, can use a
large set of patient-specific input data to identify actions yielding the greatest probability of achieving a
goal. This methodology follows a sequence of events with uncertain conditions, offering potential advantages
for personalized, patient-centered decision-making. Clinical application would require secure
integration of multiple data sources and attention to ethical considerations regarding liability for errors
and individual patient preferences.
Conclusion: Traditional decision-support tools are ill-equipped to accommodate time constraints and
uncertainty regarding diagnoses and the predicted response to treatment, both of which often impair
surgical decision-making. Decision analysis and reinforcement learning have the potential to play
complementary roles in delivering high-value surgical care through sound judgment and optimal decision-
making. |
مقاله انگلیسی |