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1 – 10 of 149Khaled Hamad Almaiman, Lawrence Ang and Hume Winzar
The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.
Abstract
Purpose
The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.
Design/methodology/approach
This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.
Findings
With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.
Research limitations/implications
Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.
Practical implications
Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.
Originality/value
Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.
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Çağla Cergibozan and İlker Gölcük
The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it…
Abstract
Purpose
The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.
Design/methodology/approach
The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.
Findings
It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.
Originality/value
This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.
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Ilyas Masudin, Putri Elma Zuliana, Dana Marsetiya Utama and Dian Palupi Restuputri
The purpose of this study is to identify the risks that exist in halal meat supply chain activities and to carry out a risk assessment using the fuzzy best-worst method (FBWM…
Abstract
Purpose
The purpose of this study is to identify the risks that exist in halal meat supply chain activities and to carry out a risk assessment using the fuzzy best-worst method (FBWM) along with mitigating risks using the risk mitigation number (RMN).
Design/methodology/approach
The method used is to collect several literature reviews related to the halal meat supply chain, which has information relevant to the risks of the meat industry in Indonesia. Then, a focus group discussion was held with several experts who play a role in the meat industry in Indonesia, and 33 identified risks were identified in halal meat supply chain activities. The proposed methodology uses FBWM and RMN in conducting risk assessment and mitigation in the meat industry in Indonesia.
Findings
The analysis reveals that priority risk is obtained by using the global weight value on the FBWM, and then risk mitigation is carried out with RMN. Priority mitigation strategies can mitigate some of the risks to the meat industry in Indonesia. The proposed mitigation strategy is designed to be more effective and efficient in preventing risks that can interfere with product halalness in halal meat supply chain activities in the Indonesian meat industry.
Research limitations/implications
The implications of this study highlight the need for collaboration among stakeholders, improved risk assessment methodologies and the expansion of research into other halal supply chains. By addressing these implications, the halal industry can enhance its integrity, consumer confidence and overall contribution to the global market.
Originality/value
This research provides an integrated approach to identifying, analyzing, assessing and mitigating risks to the meat industry in Indonesia.
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The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.
Abstract
Purpose
The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.
Design/methodology/approach
A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.
Findings
The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.
Research limitations/implications
The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.
Practical implications
From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.
Originality/value
The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.
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Atul Kumar Singh and V.R. Prasath Kumar
Blockchain is a developing technology that affects numerous industries, including facility management (FM). Many barriers are associated with adopting blockchain-enabled building…
Abstract
Purpose
Blockchain is a developing technology that affects numerous industries, including facility management (FM). Many barriers are associated with adopting blockchain-enabled building information modeling (BEBIM) in FM. This research aims to identify and prioritize the barriers to adopting BEBIM in FM.
Design/methodology/approach
To address the knowledge gap, this study employs a two-phase methodology for evaluating the barriers to adopting BEBIM in FM. The first phase involves a comprehensive literature review identifying 14 barriers to BEBIM adoption. Using a Delphi approach, the identified barriers were categorized into 6 groups and finalized by 11 experts, adding 3 more barriers to the list. The best-worst method (BWM) determines the priority weights of identified barriers and sub-barriers in the second phase.
Findings
This study reveals that adopting BEBIM for FM in India faces significant hurdles. The most critical barriers are “limited collaboration” and “communication among stakeholders,” “legal constraints in certain jurisdictions” and “challenges in establishing trust and governance models.” To mitigate these barriers, stakeholders should foster collaboration and communication, develop efficient blockchain technology (BT) and establish a trust and governance model.
Practical implications
This work underscores the importance of formulating effective strategies to overcome the identified barriers and emphasizes implications that can assist policymakers and industry stakeholders in achieving successful BEBIM adoption for improved FM practice.
Originality/value
The study provides valuable insights for policymakers, construction industry stakeholders and facility managers interested in leveraging this technology to improve the efficiency and effectiveness of FM practice in India.
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Md Kamal Hossain and Vikas Thakur
The promulgation of group purchasing organizations (GPOs) into the healthcare (HC) sector is an invaluable procurement strategy to manage the suppliers effectively. This study…
Abstract
Purpose
The promulgation of group purchasing organizations (GPOs) into the healthcare (HC) sector is an invaluable procurement strategy to manage the suppliers effectively. This study aims to identify and prioritize the factors of integrating GPOs into the HC sector on the perspectives of the developing countries such as India.
Design/methodology/approach
The factors are identified from current literature exploration, experts’ support and experience surveys. The factors are scrutinized and shortlisted using the Delphi technique and analysed further using the best-worst model method.
Findings
The findings of the study highlight the cost reduction, fair distribution of savings and healthcare supply chain (HCSC) data standardization among others to be the most prioritized drivers. The consulting services provided by GPOs including training and development as a result of high competitiveness in the HC market has been prioritized the least.
Practical implications
The study bears some important implications for decision and policymakers. The managers should consider factors, namely, cost reduction, fair distribution of savings and HCSC data standardization on a priority basis that acts as motivation for the HC providers to join the GPOs.
Originality/value
The study provides valuable insights for HC providers to participate in the GPOs for cost savings and enhance the performances.
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Sarthak Dhingra, Rakesh Raut, Angappa Gunasekaran, B. Koteswara Rao Naik and Venkateshwarlu Masuna
This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been…
Abstract
Purpose
This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been prioritized and modeled based on an extensive literature search and professional views.
Design/methodology/approach
An integrated multi-criteria decision-making approach has been used in two phases. Best worst method (BWM) is used in the first phase to prioritize the challenges with sensitivity analysis to validate the findings and eliminate a few challenges. In the second phase, interpretive structural modeling is applied to the remaining 15 challenges to obtain relative relationships among them with cross-impact matrix multiplication applied to classification analysis for their categorization.
Findings
The study’s results reveal that limited knowledge and expertise, cost and risk involved, technical issues, lack of clear regulations, resistance to change and lack of top management support are the top-ranked or high-intensity challenges according to the BWM. Interpretive structural modelling findings suggest that the lack of government initiatives has been driving other challenges with the highest driving power.
Research limitations/implications
This work has been conducted in the Indian context, so careful generalization of the results is needed.
Practical implications
This work will give health-care stakeholders a better perspective regarding blockchain’s adoption. It will help health-care stakeholders, service providers, researchers and policymakers get a glimpse of the strategies for eradicating mentioned challenges. The analysis will help reduce the challenges’ impact on blockchain’s adoption in the Indian health-care sector.
Originality/value
The adoption of BT is a novel concept, especially in developing countries such as India. This is one of the few works addressing the challenges to BT adoption in the Indian health-care sector.
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Elif Kiran, Yesim Deniz Ozkan-Ozen and Yucel Ozturkoglu
This study aims to analyze lean wastes for the poultry sector in Turkey and link lean tools to this study, focusing on identifying each lean waste that affects poultry production…
Abstract
Purpose
This study aims to analyze lean wastes for the poultry sector in Turkey and link lean tools to this study, focusing on identifying each lean waste that affects poultry production and proposing solutions for preventing these lean wastes in the sector. The proposed solutions aim to improve processes by suggesting different lean tools and their applications for the poultry sector.
Design/methodology/approach
The study consists of two different applications. First, the waste relationship matrix (WRM) was created to reveal the relationship between seven lean wastes and their importance order. Then, after determining lean tools for eliminating lean wastes, the optimum weight ranking and consistency ratio of the most suitable lean tools were calculated for these wastes and ranked with the best-worst method (BWM).
Findings
Results showed that overproduction is the most critical waste that impacts other wastes, followed by defect waste. Due to the nature of the sector, these wastes not only result in economic loss for the company but also in food waste and loss and issues related to animal welfare. Furthermore, the Kaizen approach and 5S implementation are the methods to eliminate these wastes. Detailed discussion on the link between lean tools and lean wastes is provided for the poultry sector.
Originality/value
This is the first study that theoretically and empirically identifies the potential lean waste affecting the poultry sector and provides lean tools for eliminating these wastes. Sector-specific explanations and discussions are presented in the study to show the applicability of lean approaches in the poultry sector to eliminate waste. In addition, this study is the first to integrate the WRM and BWM.
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Sheak Salman, Shah Murtoza Morshed, Md. Rezaul Karim, Rafat Rahman, Sadia Hasanat and Afia Ahsan
The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular…
Abstract
Purpose
The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.
Findings
The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.
Research limitations/implications
The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.
Originality/value
This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.
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Sanaz Tabatabaee, Mojtaba Ashour, Haleh Sadeghi, Seyed Amirali Hoseini, Saeed Reza Mohandes, Amir Mahdiyar, Syuhaida Ismail and M. Reza Hosseini
To come up with a prudent decision on the installation of an appropriate green wall (GW) on buildings, this study presents a novel decision-making algorithm. The proposed…
Abstract
Purpose
To come up with a prudent decision on the installation of an appropriate green wall (GW) on buildings, this study presents a novel decision-making algorithm. The proposed algorithm considers the importance of barriers hampering GW adoption, as well as their relationships with regard to different types of GWs existing in a contextual setting.
Design/methodology/approach
The proposed methodological approach is based on the integration of qualitative and quantitative techniques by employing focus group discussion, fuzzy-based best-worst method and fuzzy TOPSIS.
Findings
Based on the experiences of qualified experts involved in related projects in Hong Kong, the following conclusions are drawn: (1) cost, installation and maintenance-related barriers are perceived to have the highest importance, (2) modular living wall system is the most suitable GW system for the context of Hong Kong and (3) existing barriers are found to have a pivotal role in the ranking of the most suitable GW systems.
Practical implications
The findings provide valuable insight not only for policymakers and stakeholders, but also for establishing a methodological approach that can assist decision-makers in identifying the most beneficial GW system rather than the most applicable one. This could have significant implications and introduce potential changes to the common way of practice within the industry and lay the foundation for wider adoption of GW.
Originality/value
While previous studies have investigated the sustainability-related issues of GW façade applications, the current body of knowledge is deprived of a comprehensive methodological approach for the selection of the most suitable GW systems.
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