Dilip Kumar Sen, Saurav Datta and S.S. Mahapatra
Robot selection is a critical decision-making task frequently experienced in almost every industries. It has become increasingly complex due to availability of large variety of…
Abstract
Purpose
Robot selection is a critical decision-making task frequently experienced in almost every industries. It has become increasingly complex due to availability of large variety of robotic system in the present market with varying configuration, specification and flexibility. Improper selection may yield loss for the company in terms of potential profit as well as productivity. Hence, selection of an appropriate robot to suit a particular industrial application is definitely a challenging task. The paper aims to discuss these issues.
Design/methodology/approach
During robot selection, different criteria-attributes need to be taken under consideration. Criteria may be subjective or objective or a combination of both, depending on the situation. Criteria many be conflicting, in the sense that some criteria may require to be of higher value (higher-is-better), i.e. beneficial; while, others should correspond to lower values (lower-is-better), i.e. adverse or non-beneficial. Hence, the situation can be articulated as a multi-criteria decision-making problem. The specialty of Tomada de Decisión Inerativa Multicritero (TODIM) method is that it explores a global measurement of value calculable by the application of the paradigm of non-linear cumulative prospect theory. The method is based on a description, proved by empirical evidence, of how decision makers’ effectively make decisions in the face of risk.
Findings
Hence, the present work has aimed to explore the TODIM approach for industrial robot selection. Assuming all criteria have been quantitative in nature; the paper utilizes two different numeric data sets from available literature resource in perspectives of robot selection. Procedural hierarchy and application potential of the TODIM approach has been illustrated in detail in this reporting.
Originality/value
Variety of tools and techniques have already been documented in literature to solve different kinds of industrial decision-making problems; however, it seems that application of TODIM has got limited usage. Hence, application potential of TODIM has been demonstrated here in light of a robot selection problem.
Details
Keywords
Dilip Kumar Sen, Saurav Datta and S.S. Mahapatra
Recently, in turbulent and highly competitive marketplace, organizational sustainability in the long run necessitates the adaptation of appropriate supply chain (SC) strategies…
Abstract
Purpose
Recently, in turbulent and highly competitive marketplace, organizational sustainability in the long run necessitates the adaptation of appropriate supply chain (SC) strategies. Hence, traditional SC philosophies are being restructured nowadays to fulfill different business goals. Articulation of lean, agile, green and resilient SC strategies could amply be found in the literature; however, integration of those in various modes may definitely improve overall SC’s performance. Past researchers have focused on the integration of lean, agile and green paradigms together to ensure an efficient SC construct. But the integration of green and resilient paradigm has been rarely reported in the literature. To deal with the unexpected situations/disturbances in the SC management along with embedded environmental consciousness, the purpose of this paper is to integrate the resilient SC and green SC philosophies; thereof to evaluate of an overall SC “g-resilient”/“ecosilient” index for a case automotive company.
Design/methodology/approach
A consolidated list consisting of supply chain practices (combining green and resilient performance indices) have been articulated in this study. A decision-making group has been assumed; where, the role of the decision makers is to provide individuals’ judgment (subjective opinion) toward determining the weight and the rating (performance extent) of various performance indices. The overall g-resilient SC performance has been determined by computing a unique ecosilient (g-resilient) index. The concepts of fuzzy performance importance index along with Degree of Similarity (DOS) adapted from fuzzy set theory (FST) have been applied to rank various performance indicators. In addition to that, the interrelationships amongst various g-resilient indices (performance indicators) have also been established through interpretive structural modeling.
Findings
By exploring the concept of fuzzy DOS, outlined in the trapezoidal fuzzy numbers set theory, various SC performance indicators have been classified into three distinct performance categories/levels (namely regretful, tolerable, and satisfactory). Such categorization has been found helpful in order to determine ill (poor) performing SC areas, which need future improvement toward boosting up the overall g-resilient index of the company’s SC.
Originality/value
The study bears significant managerial implications. The decision support framework suggested in this paper is found capable enough to determine a unique index known as “ecosilient (g-resilient) index” toward exploring “greenness” as well as “resiliency” for the case automotive company. Application potential of the proposed ecosilient (g-resilient) index evaluation system has been explored in this reporting. The recommended framework enables the managers to cope up with unexpected disruptions and found helpful in order to reduce the environmental impacts.
Details
Keywords
Dilip Kumar Sen, Saurav Datta and S.S. Mahapatra
The purpose of this paper is to attempt supplier selection considering economic, environmental and social sustainability issues.
Abstract
Purpose
The purpose of this paper is to attempt supplier selection considering economic, environmental and social sustainability issues.
Design/methodology/approach
Subjective human judgment bears some kind of vagueness and ambiguity; fuzzy set theory has immense potential to overcome this. Owing to the advantage of intuitionistic fuzzy numbers set over classical fuzzy numbers set; three decision-making approaches have been applied here in intuitionistic fuzzy setting (namely, intuitionistic-TOPSIS, intuitionistic-MOORA and intuitionistic-GRA) to facilitate supplier selection in sustainable supply chain.
Findings
The stated objective of this research “to verify application potential of different decision support systems (in intuitionistic fuzzy setting) in the context of sustainable supplier selection” has been carried out successfully. A case empirical research has been conducted by applying three different decision-making approaches: intuitionistic fuzzy-TOPSIS, intuitionistic fuzzy-MOORA and intuitionistic fuzzy-GRA to an empirical data set of sustainable supplier selection problem. The ranking orders thus obtained through exploration of aforesaid three approaches have been explored and compared.
Originality/value
As compared to generalized fuzzy numbers, intuitionistic fuzzy numbers exhibit a membership degree, a non-membership degree and the extent of hesitation; a better way to capture inconsistency, incompleteness and imprecision of human judgment. Application potential of aforesaid three decision support approaches has been demonstrated in this reporting for a case sustainable supplier selection.
Details
Keywords
Dilip Kumar Sen, Saurav Datta, Saroj Kumar Patel and Siba Sankar Mahapatra
Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes…
Abstract
Purpose
Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes. In recent marketplace, the number of robot manufacturers has increased remarkably offering a wide range of models and specifications; thus, robot selection has become indeed confusing as well as complicated task. Selection of an appropriate robot is a sensitive process; it may result massive letdown, if not chosen properly. Therefore, for unravel the selection problem; the purpose of this paper is to explore the preference ranking organization method for enrichment evaluation (PROMETHEE) II method.
Design/methodology/approach
Apart from a large variety of robotic systems, existence of various multi-criteria decision making (MCDM) tools and techniques may create confusion to the decision makers’ in regards of application feasibility as well as superiority in performance to work under different decision-making situations. In this context, the PROMETHEE II method has been found as an efficient decision-making tool which provides complete ranking order of all available alternatives prudently, thus avoiding errors in decision making.
Findings
In this context, the present paper highlights application potential of aforesaid PROMETHEE II method in relation to robot selection problem subjected to a set of quantitative (objective) evaluation data collected from the available literature resources. Advantages and disadvantages of PROMETHEE II method have also been reported in comparison to other existing MCDM approaches.
Originality/value
The study bears significant managerial implications. Proper evaluation and selection of appropriate candidate robot would be helpful for the industries in order to improve product quality as well as to increase productivity. Proper utilization of resources could be ensured. Functioning would be accurate with reduced timespan. As a consequence, company can increase its profit margin in long run.
Details
Keywords
Dilip Kumar Sen, Saurav Datta and S.S. Mahapatra
Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated…
Abstract
Purpose
Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated since apart from objective criteria a number of subjective criteria need to be evaluated simultaneously. Plenty of decision support systems have been well documented in existing literature which considers either objective or subjective data set; however, decision support module with simultaneous consideration of objective as well as subjective data has rarely been attempted before. The paper aims to discuss these issues.
Design/methodology/approach
Motivated by this, present work exhibits application potential of preference ranking organization method for enrichment evaluations (extended to operate under fuzzy environment) to solve decision-making problems which encounter both objective as well as subjective evaluation data.
Findings
An empirical case study has been demonstrated in the context of robot selection problem. Finally, a sensitivity analysis has been performed to make the robot selection process more robust. A trade-off between objective criteria measure and subjective criteria measure has been shown using sensitivity analysis.
Originality/value
Robot selection has long been viewed as an important decision-making scenario in the industrial context. Appropriate robot selection helps in enhancing value of the product and thereby, results in increased profitability for the manufacturing industries. The proposed decision support system considering simultaneous exploration of subjective as well as objective database is rarely attempted before.
Details
Keywords
Dilip Kumar Sen and Swapan Kumar Bala
The present paper is a brief study on the modus operandi of the existing income tax audit in Bangladesh. This study centres around: meaning of tax audit; need for tax audit;…
Abstract
The present paper is a brief study on the modus operandi of the existing income tax audit in Bangladesh. This study centres around: meaning of tax audit; need for tax audit; certain conceptual issues of tax audit; existing scenario of tax audit in Bangladesh, focusing on tax system, tax audit practice, tax audit ambit, tax auditor, tax audit report, existing extent of assessment under tax audit net; and then draws a concluding line with a few recommendations. The paper reflects that the present extent of tax audit practice of Bangladesh is extremely negligible. This paper’s policy prescriptions, if followed, will hopefully provide a great boost in expanding tax audit net, which is much needed for improvement of the internal resource mobilisation in the country.
Details
Keywords
Dilip Kumar Sen, Saurav Datta and Siba Sankar Mahapatra
Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may be…
Abstract
Purpose
Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may be subjective or objective (or combination of both), depending upon the situation; requirements may also be conflicting. In practice, most of the real-world decision-making problems are based on subjective evaluation criteria which are basically ill-defined and vague. Since subjective human judgment bears ambiguity and vagueness in the decision making; application of grey numbers set theory may be proved fruitful in this context. The paper aims to discuss these issues.
Design/methodology/approach
Owing to the advantages of grey numbers set theory in tackling subjectivity in decision making; the crisp-TODIM needs to be extended by integrating with grey numbers set theory in order to facilitate decision making consisting of subjective data. Hence, the unified objective of this paper is to propose a grey-based TODIM approach in the context of decision making.
Findings
Application potential of grey-TODIM has been demonstrated through a case empirical robot selection problem. Result obtained thereof, has also been compared to that of existing grey-based decision support systems available in literature.
Originality/value
Application potential of grey-based decision support systems (grey-TOPSIS, grey analysis, grey-MOORA) have been highlighted in available literature resource. However, the shortcoming of these approaches is that they do not consider decision-makers’ risk attitude while decision making. TODIM method is derived from the philosophy of Cumulative Prospect Theory (CPT) which considers risk averting attitude of the decision maker in case of gain and risk seeking attitude in case of loss, while comparing dominance between two alternatives with respect to a particular criterion. Hence, this paper contributes a mathematical foundation of TODIM coupled with grey numbers set theory for logical decision making.
Details
Keywords
Hajam Abid Bashir, Manish Bansal and Dilip Kumar
This study aims to examine the value relevance of earnings in terms of predicting the value variables such as cash flow, capital investment (CI), dividend and stock return under…
Abstract
Purpose
This study aims to examine the value relevance of earnings in terms of predicting the value variables such as cash flow, capital investment (CI), dividend and stock return under the Indian institutional settings.
Design/methodology/approach
The study used panel Granger causality tests to examine causality relationships among variables and panel data regression models to check the statistical associations between earnings and value variables.
Findings
Based on a data set of 7,280 Bombay Stock Exchange-listed firm-years spanning over ten years from March 2009 to March 2018, the results show higher sensitivity of earnings toward cash flows, CI, divided and stock return and vice-versa. Further, the findings deduced from the empirical results demonstrate that earnings are positively related to value variables. Overall, the results established that earnings are value-relevant and have predictive ability to forecast the value variables that facilitate investors in portfolio valuation. The results are consistent with the predictive view of the value relevance of earnings. Several robustness checks confirm these results.
Originality/value
This study brings new empirical evidence from a distinct capital market, India, and provides a new facet to the value relevance debate in terms of its prediction view. The study is among earlier attempts that jointly measure the ability of earnings in forecasting different value variables by taking a uniform sample of firms at the same period. Hence, the study provides a comprehensive view of the predictive ability of reported earnings.
Details
Keywords
Dilip Kumar, Abhinav Kumar Shandilya and Thirugnanasambantham K.
The escalating global mortality rates attributed to cardiovascular diseases (CVDs) have drawn the attention of the World Health Organization (WHO), prompting researchers worldwide…
Abstract
Purpose
The escalating global mortality rates attributed to cardiovascular diseases (CVDs) have drawn the attention of the World Health Organization (WHO), prompting researchers worldwide to address this pressing health concern actively. This study aims to unravel insights into the relationship between specific diets and CVDs by examining authors, countries, articles, journal productivity and their impact.
Design/methodology/approach
Diet patterns are recognised as contributing to the rise of CVDs, prompting a comprehensive analysis of relevant literature from Scopus, Web of Science and PubMed databases using the Biblioshiny software.
Findings
The analysis delves into cluster development and major themes within the literature, encompassing holistic approaches to cardiovascular health, the nexus between diet, nutrition and cardiovascular health, the impact of plant-based diets on diverse populations, the role of the Mediterranean diet in cardiovascular health and the influence of dietary diversity on cardiovascular health across cultures.
Originality/value
Noteworthy developments in emerging areas like dietary history records, NutriOptimisation and MediCulinary Sensitivity are identified, providing a foundation for future researchers to contribute to achieving Sustainable Development Goals (SDG) 3.
Details
Keywords
– This paper aims to provide an overview of recent research on accountability of local and state governments in India.
Abstract
Purpose
This paper aims to provide an overview of recent research on accountability of local and state governments in India.
Design/methodology/approach
The Downsian theory of electoral competition is used as a departure point for classifying different sources of government accountability failures. Subsequent sections deal with each of these sources in turn: limited voter participation and awareness; ideology, honesty and competence of political parties and electoral candidates; capture by elites; clientelism and vote-buying. Each section starts by explaining the relevant departure from the Downsian framework and then reviews available empirical evidence in the Indian context for each of these possible “distortions”, besides effects of related policy interventions. The final section summarizes the lessons learnt, and the fresh questions that they raise.
Findings
The paper describes a range of possible reasons that limit the effectiveness of elections as a mechanism inducing governments to be accountable to their citizens and reviews the evidence available from the Indian context concerning each of these.
Originality/value
The contribution of the paper is to provide an overview and perspective of recent literature on political economy problems affecting performance of state and local governments in India.