Financial performance of the textile industry in India: the case of Haryana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ishwar Singh Darji ◽  
Suman Dahiya
Keyword(s):  
Decision Making ◽  
Financial Performance ◽  
Textile Industry ◽  
Design Methodology ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Content Type ◽  
Key Stakeholders ◽  
Private And Public ◽  
Technical Efficiency Score

Purpose This study aims to evaluate the financial performance of the textile industry in Haryana located in the northern part of India. Design/methodology/approach Input-oriented Cooper, Charnes and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) techniques of data envelopment analysis, as well as the return to scale (RTS) technique, were used to conduct the analysis. Findings The findings show that textile units in Haryana have hugely underperformed financially with a consolidated technical efficiency score of only 0.35. Both private and public limited textile companies with respective scores of 0.46 and 0.24 are technically efficient. Public limited textile companies are more efficient than private limited companies. Private limited textile companies need to increase their input scale because they are operating at an increasing return to scale while public limited textile companies have to lower their input scale because most companies are operating at a decreasing return to scale to enhance their efficiency. Originality/value The study can assist in decision-making to all key stakeholders (Shareholders, management, government, tax authorities, debtors and creditors, among others) by identifying efficient and inefficient companies. Appropriate policies can be framed based on that knowledge.

Fuzzy C-means based data envelopment analysis for mitigating the impact of units’ heterogeneity

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 536-551 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Shide Sadat Hashemi ◽  
Hannan Amoozad Mahdiraji
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Negative Impact ◽  
Positive Impact ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Content Type ◽  
Fuzzy C Means ◽  
The Impact ◽  
Decision Making Units

Purpose – Data envelopment analysis (DEA) is a non-parametric model that is developed for evaluating the relative efficiency of a set of homogeneous decision-making units that each unit transforms multiple inputs into multiple outputs. However, usually the decision-making units are not completely similar. The purpose of this paper is to propose an algorithm for DEA applications when considered DMUs are non-homogeneous. Design/methodology/approach – To reach this aim, an algorithm is designed to mitigate the impact of heterogeneity on efficiency evaluation. Using fuzzy C-means algorithm, a fuzzy clustering is obtained for DMUs based on their inputs and outputs. Then, the fuzzy C-means based DEA approach is used for finding the efficiency of DMUs in different clusters. Finally, the different efficiencies of each DMU are aggregated based on the membership values of DMUs in clusters. Findings – Heterogeneity causes some positive impact on some DMUs while it has negative impact on other ones. The proposed method mitigates this undesirable impact and a different distribution of efficiency score is obtained that neglects this unintended impacts. Research limitations/implications – The proposed method can be applied in DEA applications with a large number of DMUs in different situations, where some of them enjoyed the good environmental conditions, while others suffered from bad conditions. Therefore, a better assessment of real performance can be obtained. Originality/value – The paper proposed a hybrid algorithm combination of fuzzy C-means clustering method with classic DEA models for the first time.

Financial performance evaluation of companies listed on Tehran Stock Exchange

2018 ◽  
Vol 60 (3) ◽  
pp. 885-900 ◽  
Author(s):  
Ali Karimi ◽  
Masoud Barati
Keyword(s):  
Performance Evaluation ◽  
Financial Performance ◽  
Design Methodology ◽  
Stock Exchange ◽  
Financial Information ◽  
Data Envelopment ◽  
Negative Data ◽  
Content Type ◽  
Financial Measures ◽  
Financial Metrics

Purpose This paper aims to evaluate the financial performance of companies listed on Tehran Stock Exchange by using negative data envelopment analysis (DEA) approach. Design/methodology/approach First, the financial metrics for performance evaluation were extracted and then filtered based on the experts’ opinions. Upon choosing the appropriate financial measures, the financial information of 72 companies selected from four automotive, pharmaceutical, petrochemical and cement industries were collected, and the criteria values were also measured. The financial performance of selected companies was assessed using negative data bounded adjusted measure in the DEA, and efficient and inefficient companies were identified. Finally, the efficient companies were ranked using Andersen and Petersen model. Findings The required analysis was conducted, and the financial performance of selected companies listed on Tehran Stock Exchange was evaluated. There were 58 efficient companies with a performance value of 1; 14 companies became inefficient because the efficiency size was less than 1; therefore, reference units were also introduced to the managers for efficiency of inefficient companies. Originality/value The aim of this study was to identify the required financial criteria and to determine an appropriate model for performance evaluation based on negative DEA. The findings can help shareholders to identify efficient companies and make the optimal portfolio accordingly; the managers of inefficient companies can also take the proper reforming actions to improve efficiency.

Evaluating after-sales service units by developing inverse network data envelopment analysis model

2019 ◽  
Vol 27 (2) ◽  
pp. 695-707 ◽  
Author(s):  
Reza Farzipoor Saen ◽  
Seyed Shahrooz Seyedi Hosseini Nia
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Content Type ◽  
Network Data Envelopment Analysis ◽  
Decision Making Unit

Purpose The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant. Findings The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided. Originality/value This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

A benchmarking study of Indian seaports

2019 ◽  
Vol 13 (1) ◽  
pp. 88-102
Author(s):  
Sajeev Abraham George ◽  
Anurag C. Tumma
Keyword(s):  
Financial Performance ◽  
Future Research ◽  
Data Envelopment ◽  
Operational Parameters ◽  
Two Stage ◽  
Content Type ◽  
The Public ◽  
Port Authorities ◽  
Financial Performance Measures ◽  
The Government

Purpose The purpose of this paper is to benchmark the operational and financial performances of the major Indian seaports to help derive useful insights to improve their performance. Design/methodology/approach A two-stage data envelopment analysis (DEA) methodology has been used with the help of data collected on the 13 major seaports of India. The first stage of the DEA captured the operational efficiencies, while the second stage the financial performance. Findings A window analysis over a period of three years revealed that no port was able to score an overall average efficiency of 100 per cent. The study identified the better performing units among their peers in both the stages. The contrasting results of the study with the traditional operational and financial performance measures used by the ports helped to derive useful insights. Research limitations/implications The data used in the study were majorly limited to the available sources in the public domain. Also, the study was limited to the major seaports which are under the Government of India and no comparisons were carried out with other local or international ports. Practical implications There is a need to prioritize investments and improvement efforts where they are most needed, instead of following a generalized approach. Once the benchmark ports are identified, the port authorities and other relevant stakeholders should work in detail on the factors causing inefficiencies, for possible improvements in performance. Originality/value This paper carried out a two-stage DEA that helped to derive useful insights on operational efficiency and financial performance of the India seaports. A combination of the financial and operational parameters, along with a comparison of the DEA results with the traditional measures, provided a different perspective on the Indian seaport performance. Considering the scarcity of research papers reported in the literature on DEA-based benchmarking studies of seaports in the Indian context, it has the potential to attract future research in this field.

Employing needs-based funding formulae – some unavoidable tradeoffs

2017 ◽  
Vol 31 (7) ◽  
pp. 1092-1102
Author(s):  
Tal Gilead ◽  
Iris BenDavid-Hadar
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Design Methodology ◽  
Social Equity ◽  
School Resources ◽  
Content Type ◽  
Funding Formula ◽  
Policy Goals ◽  
Theoretical Investigations ◽  
Schooling System

Purpose The method by which the state allocates resources to its schooling system can serve as an important instrument for achieving desired improvements in levels of educational attainment, social equity and other social policy goals. In many school systems, the allocation of school resources is done according to a needs-based funding formula. The purpose of this paper is to provide a deeper understanding of some significant tradeoffs involved in employing needs-based funding formulae. Design/methodology/approach The paper is based on theoretical investigations of normative aspects involved in using needs-based funding formulae. Findings There are a number of underexplored complications and difficulties that arise from the use of needs-based funding formulae. Dealing with these involves significant tradeoffs that require taking normative decisions. Understanding these tradeoffs is important for improving the use of needs-based funding formulae. Originality/value The paper highlights three under-examined issues that emerge from the current use of needs-based funding formulae. These issues are: to what extent funding formulae should be responsive to social and economic needs? To what extent should funding formulae allow for the use of discretion in resource allocation? To what degree needs-based formulae funding should be linked to outcomes? By discussing these issues and the tradeoffs involved in them, the paper provides a deeper understanding of significant aspects stemming from the use of needs-based funding formulae. This, in turn, can serve as a basis for an improved and better informed process for decision making regarding the use of funding formulae.

Has Lean improved organizational decision making?

2016 ◽  
Vol 29 (5) ◽  
pp. 536-549 ◽  
Author(s):  
Pascale Simons ◽  
Jos Benders ◽  
Jochen Bergs ◽  
Wim Marneffe ◽  
Dominique Vandijck
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Lean Management ◽  
Structured Interviews ◽  
Organizational Decision Making ◽  
Content Type ◽  
Organizational Contexts ◽  
Sustainable Improvement ◽  
Care Processes ◽  
Practical Implications

Purpose – Sustainable improvement is likely to be hampered by ambiguous objectives and uncertain cause-effect relations in care processes (the organization’s decision-making context). Lean management can improve implementation results because it decreases ambiguity and uncertainties. But does it succeed? Many quality improvement (QI) initiatives are appropriate improvement strategies in organizational contexts characterized by low ambiguity and uncertainty. However, most care settings do not fit this context. The purpose of this paper is to investigate whether a Lean-inspired change program changed the organization’s decision-making context, making it more amenable for QI initiatives. Design/methodology/approach – In 2014, 12 professionals from a Dutch radiotherapy institute were interviewed regarding their perceptions of a Lean program in their organization and the perceived ambiguous objectives and uncertain cause-effect relations in their clinical processes. A survey (25 questions), addressing the same concepts, was conducted among the interviewees in 2011 and 2014. The structured interviews were analyzed using a deductive approach. Quantitative data were analyzed using appropriate statistics. Findings – Interviewees experienced improved shared visions and the number of uncertain cause-effect relations decreased. Overall, more positive (99) than negative Lean effects (18) were expressed. The surveys revealed enhanced process predictability and standardization, and improved shared visions. Practical implications – Lean implementation has shown to lead to greater transparency and increased shared visions. Originality/value – Lean management decreased ambiguous objectives and reduced uncertainties in clinical process cause-effect relations. Therefore, decision making benefitted from Lean increasing QI’s sustainability.

Boosting the financial performance of B2B SMEs

2018 ◽  
Vol 34 (7) ◽  
pp. 32-34
Keyword(s):  
Financial Performance ◽  
Design Methodology ◽  
Reading Time ◽  
Brand Orientation ◽  
Content Type ◽  
Financial Outcomes ◽  
External Communication ◽  
Brand Credibility ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings SMEs operating in the B2B context are able to boost financial outcomes by adopting a branding approach. Strong brand orientation and an emphasis on internal and external communication increases awareness and the brand credibility that can ultimately enhance business and financial performance. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Jumping to conclusions – an analysis of the NBA Draft Combine athleticism data and its influence on managerial decision-making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tobias Berger ◽  
Frank Daumann
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Predictive Power ◽  
Principal Component ◽  
Decision Makers ◽  
Decision Quality ◽  
Managerial Behavior ◽  
Managerial Decision ◽  
Content Type ◽  
Selection Behavior

PurposeThe NBA Draft policy pursues the goal to provide the weakest teams with the most talented young players to close the gap to the superior competition. But it hinges on appropriate talent evaluation skills of the respective organizations. Research suggests the policy might be valid but to date unable to produce its intended results due to the “human judgement-factor”. This paper investigates specific managerial selection-behavior-influencing information to examine why decision-makers seem to fail to constantly seize the opportunities the draft presents them with.Design/methodology/approachAthleticism data produced within the NBA Draft Combine setting is strongly considered in the player evaluations and consequently informs the draft decisions of NBA managers. Curiously, research has failed to find much predictive power within the players pre-draft combine results for their post-draft performance. This paper investigates this clear disconnect, by examining the pre- and post-draft data from 2000 to 2019 using principal component and regression analysis.FindingsEvidence for an athletic-induced decision-quality-lowering bias within the NBA Draft process was found. The analysis proves that players with better NBA Draft Combine results tend to get drafted earlier. Controlling for position, age and pre-draft performance there seems to be no proper justification based on post-draft performance for this managerial behavior. This produces systematic errors within the structure of the NBA Draft process and leads to problematic outcomes for the entire league-policy.Originality/valueThe paper delivers first evidence for an athleticism-induced decision-making bias regarding the NBA Draft process. Informing future selection-behavior of managers this research could improve NBA Draft decision-making quality.

Are the saving decision patterns of bank customers also clouded by psychological biases? Evidence from Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joseph Emmanuel Tetteh ◽  
Christopher Boachie
Keyword(s):  
Decision Making ◽  
Loss Aversion ◽  
Design Methodology ◽  
Weighted Least Squares ◽  
Least Squares Regression ◽  
Individual Decision ◽  
Content Type ◽  
Saving Decisions ◽  
The Individual ◽  
Practical Implications

PurposeThis paper attempts to investigate the influence of psychological biases on saving decision-making of bank customers in Ghana.Design/methodology/approachIt employs weighted least squares regression to test the effect of psychological biases on savings decisions of bank customers.FindingsThe findings show that all the nine psychological biases, namely mental accounting, availability, loss aversion, representativeness, anchoring, overconfidence, status quo, framing effect and disposition effect employed for the study have a significant influence on saving decision of bank customers. The results depict that psychological biases are entrenched in the saving pattern of bank customers in Ghana.Practical implicationsFor policy purposes, the study recommends that bank customers need to enhance their knowledge of psychological biases in order to improve their gains from savings, and not to fall prey to these prejudices. The satisfied customer is a dependable source of bank viability and survival.Originality/valueTo the best of the knowledge of the author, this study provides the first empirical evidence of the influence of psychological biases on saving decisions of bank customers in Ghana. The findings of this study will enhance knowledge on the influence of psychological biases on individual decision-making and will accentuate the fact that the individual is not an entirely rational being.

Technical efficiency and its determinants in the Indian textile garments industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdulla ◽  
Shiv Kumar
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Textile Industry ◽  
Small And Medium Enterprises ◽  
Stochastic Frontier ◽  
Efficiency Score ◽  
Value Chains ◽  
Small Scale ◽  
Content Type ◽  
Medium Enterprises

Purpose This paper aims to examine technical efficiency and its determinants in Indian textile garments industry in post-agreement on textiles and clothing regime and evaluate the technical efficiency among micro, small and medium enterprises (MSMEs) firms. Design/methodology/approach This study uses unbalanced panel data for the period 2005–2010 to 2015–2016. The stochastic frontier function is used to estimate technical efficiency and its determinants. Findings The results show that the overall ecosystem of textile garments’ value chains could be improved to enhance the technical efficiency thereof. The result also reveals that small-scale firms have the highest technical efficiency scores, and medium-scale firms have the least technical efficiency score among all the categories of MSMEs. Research limitations/implications The textile garments industry needs to define its innovation strategies, as these strategies lead to different results that can be achieved only through the management of resources dedicated to the generation and implementation of innovations. Practical implications This study has shown that to offset India’s cost disadvantage in the international markets, there is a need to develop an ecosystem of textile manufacturing and value chains, eliminate the inverted duty structure (where inputs are taxed at a higher rate than the final product) and switch over from shuttle looms toward shuttle-less looms. This would unleash the potential of textile and garments industry and make it globally competitive and technically efficient. Further, there will be an alignment with the ease of doing business with an appropriate mix of policy, technology, institution, infrastructure, information and services. Originality/value Using frontier production function takes stochastic context into account for the dynamic character of technical efficiency and its components. Most of the past studies have assessed technical efficiency at the aggregate level using three-digit National Industrial Classification (NIC) or four-digit NIC code. An analysis at higher levels of aggregation masks the variation in technical efficiency. This study used five-digit NIC data to measure the firm-specific technical efficiency of the textile industry. According to the authors’ knowledge, this study is the first of its kind in the Indian textile industry using stochastic frontier approach and panel data. Further, it also looks at the contribution of different determinants in technical efficiency to the firms.

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