Pub Date : 2023-01-17DOI: 10.1108/jamr-06-2022-0124
M. Puviarasu, P. Asokan, S. Sherif, K. Mathiyazhagan, P. Sasikumar
PurposeIncreased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental benefits. This scenario has forced the battery industries to collect used batteries and establish the formal battery recycling plant (BRP) for effective recycling. The starting of BRP includes several strategic decisions, one of the most critical decisions encountered is to find the best sustainable location for BRP. Hence, this paper aims to address the complexity of the issues faced during the BRP location selection through a hybrid framework.Design/methodology/approachIn this study, the criteria are identified under socio-cultural, technical, environmental, economic and policy and legal (STEEP) dimensions through literature review and experts' opinions. Then, the hybrid methodology integrating fuzzy decision making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and technique for order preference by similarity to an ideal solution (TOPSIS) has been proposed to find the inter-relationship between criteria, the weights of criteria and the best alternative.FindingsThe identified five main criteria and 26 sub-criteria have been analyzed through fuzzy DEMATEL, and found that the policy and legal criteria have more inter-relationship with other criteria. Then from BWM results, it is found that the support from government bodies has attained the maximum weightage. Finally, the second alternative has been identified as a more suitable location for establishing BRP using TOPSIS. Further, it is found from the results that the support from government bodies, the impact of emissions, availability of basic facilities and community health are the essential criteria under STEEP dimensions for establishing BRP.Originality/valueIn addition to the various existing sustainable criteria, this study has also considered a set of policy and legal criteria for the evaluation of locations for BRP. Further, the hybrid MCDM method has been proposed in this study for selecting the best alternative. Thus, this study has yielded more insights to the decision-makers in choosing a sustainable location for BRP.
{"title":"A STEEP based hybrid multi-criteria decision making model for the evaluation of battery recycling plant location","authors":"M. Puviarasu, P. Asokan, S. Sherif, K. Mathiyazhagan, P. Sasikumar","doi":"10.1108/jamr-06-2022-0124","DOIUrl":"https://doi.org/10.1108/jamr-06-2022-0124","url":null,"abstract":"PurposeIncreased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental benefits. This scenario has forced the battery industries to collect used batteries and establish the formal battery recycling plant (BRP) for effective recycling. The starting of BRP includes several strategic decisions, one of the most critical decisions encountered is to find the best sustainable location for BRP. Hence, this paper aims to address the complexity of the issues faced during the BRP location selection through a hybrid framework.Design/methodology/approachIn this study, the criteria are identified under socio-cultural, technical, environmental, economic and policy and legal (STEEP) dimensions through literature review and experts' opinions. Then, the hybrid methodology integrating fuzzy decision making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and technique for order preference by similarity to an ideal solution (TOPSIS) has been proposed to find the inter-relationship between criteria, the weights of criteria and the best alternative.FindingsThe identified five main criteria and 26 sub-criteria have been analyzed through fuzzy DEMATEL, and found that the policy and legal criteria have more inter-relationship with other criteria. Then from BWM results, it is found that the support from government bodies has attained the maximum weightage. Finally, the second alternative has been identified as a more suitable location for establishing BRP using TOPSIS. Further, it is found from the results that the support from government bodies, the impact of emissions, availability of basic facilities and community health are the essential criteria under STEEP dimensions for establishing BRP.Originality/valueIn addition to the various existing sustainable criteria, this study has also considered a set of policy and legal criteria for the evaluation of locations for BRP. Further, the hybrid MCDM method has been proposed in this study for selecting the best alternative. Thus, this study has yielded more insights to the decision-makers in choosing a sustainable location for BRP.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45980679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-13DOI: 10.1108/jamr-07-2022-0150
Seerat Fatima, M. Hassan
PurposeThere is a growing array of literature that supports various implications of positive organizational psychology on workplace outcomes such as the positive work cultures. However, lack of appropriate measuring instruments is halting the progress in this field. Laid down in this article are the conceptual and empirical perspective regarding a positive group culture, i.e. meaningful group culture (MGC) and elaboration of what MGC is and how to measure it. For this study, the MGC is defined as a culture of humane orientation and explained through five dimensions: ideology infused, caring for employees, pro diversity, helping and employee-centric organization identification. The purpose of this paper is to address this issue.Design/methodology/approachTo further elucidate, development and validation of the MGC instrument was carried out in three phases. In the very first phase, content and face validity was assessed by experts. Following it, the second phase construct validity was undertaken through exploratory factor analysis of the results from the use of the instrument on a sample of 540 professionals. To end with, in the third phase, multilevel confirmatory analysis was conducted on an organizational sample of 397 individuals and 106 groups.FindingsThe results of the Multilevel Confirmatory Factor Analysis (MCFA) provided further evidence of confirmation that the extraction of five factors was appropriate, and reliability analysis showed the MGC to be both valid and reliable. Consequently, the applications of the tool to Human Resource Development (HRD) professionals are suggested.Research limitations/implicationsTo broaden the coverage and enhance generalizability, the study focused on multi-sector convenient based sample.Practical implicationsHRD professionals can use it as a diagnostic tool for deeper exploration into systematic and organizational issues. The use of it can provide a window for addressing the developmental needs within the organizations.Originality/valueThis study is possibly one of the first to develop a psychometrically valid scale to measure higher order measure of a work group culture through multilevel assessment of the model.
{"title":"Meaningful group culture: development of a multidimensional measure using multilevel assessment","authors":"Seerat Fatima, M. Hassan","doi":"10.1108/jamr-07-2022-0150","DOIUrl":"https://doi.org/10.1108/jamr-07-2022-0150","url":null,"abstract":"PurposeThere is a growing array of literature that supports various implications of positive organizational psychology on workplace outcomes such as the positive work cultures. However, lack of appropriate measuring instruments is halting the progress in this field. Laid down in this article are the conceptual and empirical perspective regarding a positive group culture, i.e. meaningful group culture (MGC) and elaboration of what MGC is and how to measure it. For this study, the MGC is defined as a culture of humane orientation and explained through five dimensions: ideology infused, caring for employees, pro diversity, helping and employee-centric organization identification. The purpose of this paper is to address this issue.Design/methodology/approachTo further elucidate, development and validation of the MGC instrument was carried out in three phases. In the very first phase, content and face validity was assessed by experts. Following it, the second phase construct validity was undertaken through exploratory factor analysis of the results from the use of the instrument on a sample of 540 professionals. To end with, in the third phase, multilevel confirmatory analysis was conducted on an organizational sample of 397 individuals and 106 groups.FindingsThe results of the Multilevel Confirmatory Factor Analysis (MCFA) provided further evidence of confirmation that the extraction of five factors was appropriate, and reliability analysis showed the MGC to be both valid and reliable. Consequently, the applications of the tool to Human Resource Development (HRD) professionals are suggested.Research limitations/implicationsTo broaden the coverage and enhance generalizability, the study focused on multi-sector convenient based sample.Practical implicationsHRD professionals can use it as a diagnostic tool for deeper exploration into systematic and organizational issues. The use of it can provide a window for addressing the developmental needs within the organizations.Originality/valueThis study is possibly one of the first to develop a psychometrically valid scale to measure higher order measure of a work group culture through multilevel assessment of the model.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46464092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-01DOI: 10.1108/jamr-05-2022-0095
A. Patel, Anurag Singh, Satyanarayana Parayitam
PurposeThe study's objective is to examine the consumers' intention to buy counterfeit brand shoes. A conceptual model is developed to test the risk-taking and word-of-mouth (WOM) as a moderator in the relationship between status consumption, brand image, and consumer intention to buy counterfeit shoes.Design/methodology/approachBased on the theory of reasoned action (TRA) and signaling theory (ST), this research was conducted in the Indian National Capital Region. Using a structured instrument, the data was collected from 240 respondents. After checking the psychometric properties of the survey instrument using the Lisrel package of structural equation modeling, Hayes's PROCESS macros were used for testing the hypotheses.FindingsThe findings from the study indicate that (1) status consumption and brand image are positively associated with purchase intention of counterfeit brand shoes, and (2) risk-taking moderates the relationship between (1) status consumption and purchase intention, and (2) brand image and purchase intension, (3) significant three-way interaction between WOM, risk-taking and status consumption on purchase intention, and (4) significant three-way interaction between brand image, WOM, and risk-taking on purchase intention of counterfeit brand shoes.Research limitations/implicationsAs with any survey research, this study has common method variance as a potential problem. However, through the latent variable method and Harman's single-factor analysis, the common method variance was checked. The study has several implications for managers, e-marketers, and consumers.Practical implicationsThe study has several implications for marketers selling counterfeit products and managers intending to protect their branded products.Originality/valueA conceptual model showing two-way and three-way interactions between status consumption, risk-taking, and WOM influencing the consumer purchase intention of counterfeit products was discussed. This is the first of its kind in India to explore such relationships.
{"title":"Risk-taking and WOM as moderators in the relationship between status consumption, brand image and purchase intention of counterfeit brand shoes","authors":"A. Patel, Anurag Singh, Satyanarayana Parayitam","doi":"10.1108/jamr-05-2022-0095","DOIUrl":"https://doi.org/10.1108/jamr-05-2022-0095","url":null,"abstract":"PurposeThe study's objective is to examine the consumers' intention to buy counterfeit brand shoes. A conceptual model is developed to test the risk-taking and word-of-mouth (WOM) as a moderator in the relationship between status consumption, brand image, and consumer intention to buy counterfeit shoes.Design/methodology/approachBased on the theory of reasoned action (TRA) and signaling theory (ST), this research was conducted in the Indian National Capital Region. Using a structured instrument, the data was collected from 240 respondents. After checking the psychometric properties of the survey instrument using the Lisrel package of structural equation modeling, Hayes's PROCESS macros were used for testing the hypotheses.FindingsThe findings from the study indicate that (1) status consumption and brand image are positively associated with purchase intention of counterfeit brand shoes, and (2) risk-taking moderates the relationship between (1) status consumption and purchase intention, and (2) brand image and purchase intension, (3) significant three-way interaction between WOM, risk-taking and status consumption on purchase intention, and (4) significant three-way interaction between brand image, WOM, and risk-taking on purchase intention of counterfeit brand shoes.Research limitations/implicationsAs with any survey research, this study has common method variance as a potential problem. However, through the latent variable method and Harman's single-factor analysis, the common method variance was checked. The study has several implications for managers, e-marketers, and consumers.Practical implicationsThe study has several implications for marketers selling counterfeit products and managers intending to protect their branded products.Originality/valueA conceptual model showing two-way and three-way interactions between status consumption, risk-taking, and WOM influencing the consumer purchase intention of counterfeit products was discussed. This is the first of its kind in India to explore such relationships.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49666848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-31DOI: 10.1108/jamr-05-2022-0088
Chaitanya Arun Sathe, Chetan Panse
PurposeThe objective of the study is to analyze the impact of the adoption of the Agile Mindset on the productivity of Agile software development teams in IT enterprises during COVID-19.Design/methodology/approachA web-based survey is performed with voluntary participants working with the Agile software development professionals with a specific focus on IT enterprises around Pune, India. For this the initial exploratory literature review was performed, to explore the team's behaviors and their response to the crises like the Covid-19 pandemic. Data is collected from the targeted population using the random sampling method. A questionnaire is designed with the help of a five-point Likert scale. All the respondents were analyzed based on their behaviors shown and how adopting to Agile mindset has impacted their productivity during the pandemic. Collected data would be then analyzed using the Smart PLS-SEM methodology.FindingsFindings of the study show that Agile software development teams adopting to Agile mindset are better at responding to crisis and quick to adapt to change as teams adopting the Agile mindset is likely to sustain or even improve their productivity during the crises like Covid-19 pandemic. Adapting to an Agile mindset is important for Agile software development teams during a crisis as a response to changes in the working as well as environmental conditions. This study also shows that by adopting an Agile mindset, development teams are better at responding to the crisis eventually improving productivity.Research limitations/implicationsResearch limitations for this study-scope of the study could be extended to the larger population across geographies to have improved insights Productivity Factors like- Efforts Efficiency, Backlog-management Index (BMI), and Weighted Average Productivity (VWP) for team members can be included. More behavioral factors for Agile Mindset can be considered.Practical implicationsAgile software development teams are characterized by collaboration and responsibility. Recent enforcement of pandemic precautionary measures has enforced Agile software development teams to work remotely and maintain social distancing while in the office. It was challenging for most of the working people to adjust to the new working conditions (Yang et al., 2021) However, in IT organizations, adopting the Agile mindset has ensured continuous software deliveries, took ownership, and quickly adapted to the volatile situations, ultimately resulting into the growth in the productivity unlike to that of other sectors of the economy.Social implicationsIn this study, we have analyzed the hypotheses with statistical significance in association with constructs that are in sync with the available literature. Adopting the Agile mindset values has positively impacted the team's behavior resulting in productivity improvement even in the distributed working locations in pandemic situations.Originality/valueThe study highlights that adopting
{"title":"Analyzing the impact of agile mindset adoption on software development teams productivity during COVID-19","authors":"Chaitanya Arun Sathe, Chetan Panse","doi":"10.1108/jamr-05-2022-0088","DOIUrl":"https://doi.org/10.1108/jamr-05-2022-0088","url":null,"abstract":"PurposeThe objective of the study is to analyze the impact of the adoption of the Agile Mindset on the productivity of Agile software development teams in IT enterprises during COVID-19.Design/methodology/approachA web-based survey is performed with voluntary participants working with the Agile software development professionals with a specific focus on IT enterprises around Pune, India. For this the initial exploratory literature review was performed, to explore the team's behaviors and their response to the crises like the Covid-19 pandemic. Data is collected from the targeted population using the random sampling method. A questionnaire is designed with the help of a five-point Likert scale. All the respondents were analyzed based on their behaviors shown and how adopting to Agile mindset has impacted their productivity during the pandemic. Collected data would be then analyzed using the Smart PLS-SEM methodology.FindingsFindings of the study show that Agile software development teams adopting to Agile mindset are better at responding to crisis and quick to adapt to change as teams adopting the Agile mindset is likely to sustain or even improve their productivity during the crises like Covid-19 pandemic. Adapting to an Agile mindset is important for Agile software development teams during a crisis as a response to changes in the working as well as environmental conditions. This study also shows that by adopting an Agile mindset, development teams are better at responding to the crisis eventually improving productivity.Research limitations/implicationsResearch limitations for this study-scope of the study could be extended to the larger population across geographies to have improved insights Productivity Factors like- Efforts Efficiency, Backlog-management Index (BMI), and Weighted Average Productivity (VWP) for team members can be included. More behavioral factors for Agile Mindset can be considered.Practical implicationsAgile software development teams are characterized by collaboration and responsibility. Recent enforcement of pandemic precautionary measures has enforced Agile software development teams to work remotely and maintain social distancing while in the office. It was challenging for most of the working people to adjust to the new working conditions (Yang et al., 2021) However, in IT organizations, adopting the Agile mindset has ensured continuous software deliveries, took ownership, and quickly adapted to the volatile situations, ultimately resulting into the growth in the productivity unlike to that of other sectors of the economy.Social implicationsIn this study, we have analyzed the hypotheses with statistical significance in association with constructs that are in sync with the available literature. Adopting the Agile mindset values has positively impacted the team's behavior resulting in productivity improvement even in the distributed working locations in pandemic situations.Originality/valueThe study highlights that adopting","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42247425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-27DOI: 10.1108/jamr-01-2022-0010
G. Prakash, Kumar Ambedkar
PurposeThis paper explores the relationships between Industry 4.0-driven technologies and the circular economy-driven business model (CEDBM) components of value creation, delivery and capture along manufacturing processes.Design/methodology/approachBased on the literature, a research model is developed in which the three CEBDM components are represented by five components: product service system (PSS), product design, industrial symbiosis (IS), consumer interaction and pay-per-use/rental. For each of these five components, enabling Industry 4.0 technologies are identified and vague interdependence relationships were assessed using a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method.FindingsThis paper contributes to the literature by exploring the relationships of the CEDBM components of value creation, value delivery and value capture with Industry 4.0-driven technological enablers. In addition, causal relationships between Industry 4.0 technologies and their relevance for facilitating CE-enabled manufacturing processes are identified, and finally, Industry 4.0-driven technological enablers of CE are categorized as base and front-end technologies.Research limitations/implicationsThe findings suggest that value delivery-based differentiation provides new avenues for value creation and innovative forms of value capture in CEDBMs.Practical implicationsPractitioners can use the findings to develop a roadmap for Industry 4.0-driven technological solutions for CE.Social implicationsCE-driven processes of manufacturing provide not only opportunities for value capture, creation and delivery but also avenues for customer-centric product and service development and effective resource utilization.Originality/valueThis paper is the first to identify value creation, delivery and capture processes along with Industry 4.0-enabled manufacturing processes.
{"title":"Digitalization of manufacturing for implanting value, configuring circularity and achieving sustainability","authors":"G. Prakash, Kumar Ambedkar","doi":"10.1108/jamr-01-2022-0010","DOIUrl":"https://doi.org/10.1108/jamr-01-2022-0010","url":null,"abstract":"PurposeThis paper explores the relationships between Industry 4.0-driven technologies and the circular economy-driven business model (CEDBM) components of value creation, delivery and capture along manufacturing processes.Design/methodology/approachBased on the literature, a research model is developed in which the three CEBDM components are represented by five components: product service system (PSS), product design, industrial symbiosis (IS), consumer interaction and pay-per-use/rental. For each of these five components, enabling Industry 4.0 technologies are identified and vague interdependence relationships were assessed using a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method.FindingsThis paper contributes to the literature by exploring the relationships of the CEDBM components of value creation, value delivery and value capture with Industry 4.0-driven technological enablers. In addition, causal relationships between Industry 4.0 technologies and their relevance for facilitating CE-enabled manufacturing processes are identified, and finally, Industry 4.0-driven technological enablers of CE are categorized as base and front-end technologies.Research limitations/implicationsThe findings suggest that value delivery-based differentiation provides new avenues for value creation and innovative forms of value capture in CEDBMs.Practical implicationsPractitioners can use the findings to develop a roadmap for Industry 4.0-driven technological solutions for CE.Social implicationsCE-driven processes of manufacturing provide not only opportunities for value capture, creation and delivery but also avenues for customer-centric product and service development and effective resource utilization.Originality/valueThis paper is the first to identify value creation, delivery and capture processes along with Industry 4.0-enabled manufacturing processes.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46377940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-13DOI: 10.1108/jamr-04-2022-0074
Maman Alimansyah, Yoshi Takahashi
PurposeThis study examines how perceived organizational justice mediates the relationship between talent management (TM) and non-high potential employees (NHPE) outcomes (i.e. affective commitment, job satisfaction, and the intention to leave) in the public sector, thereby clarifying the underlying mechanisms.Design/methodology/approachThe authors conducted a causal mediation analysis of the findings of a scenario-based survey with 748 public-sector NHPEs by adopting a post-test experimental design.FindingsPerceived distributive justice and perceived procedural justice mediated the relationships among equal resource distribution/TM procedures and NHPE outcomes, respectively.Originality/valueThis study extends and clarifies the argument for fairness judgments based on the gap in resource allocation and the presence or absence of the six rules of procedural justice that affect the attitudes and behaviors of NHPEs, who are generally more affected by TM but underexplored, in the public sector in which NHPEs are considered to be more sensitive to TM due to the egalitarian culture of public sector.
{"title":"How does perceived organizational justice mediate talent management of non-high potential employees and their outcomes?","authors":"Maman Alimansyah, Yoshi Takahashi","doi":"10.1108/jamr-04-2022-0074","DOIUrl":"https://doi.org/10.1108/jamr-04-2022-0074","url":null,"abstract":"PurposeThis study examines how perceived organizational justice mediates the relationship between talent management (TM) and non-high potential employees (NHPE) outcomes (i.e. affective commitment, job satisfaction, and the intention to leave) in the public sector, thereby clarifying the underlying mechanisms.Design/methodology/approachThe authors conducted a causal mediation analysis of the findings of a scenario-based survey with 748 public-sector NHPEs by adopting a post-test experimental design.FindingsPerceived distributive justice and perceived procedural justice mediated the relationships among equal resource distribution/TM procedures and NHPE outcomes, respectively.Originality/valueThis study extends and clarifies the argument for fairness judgments based on the gap in resource allocation and the presence or absence of the six rules of procedural justice that affect the attitudes and behaviors of NHPEs, who are generally more affected by TM but underexplored, in the public sector in which NHPEs are considered to be more sensitive to TM due to the egalitarian culture of public sector.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44426977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-06DOI: 10.1108/jamr-03-2022-0054
Ami A. Kumar, Anupriya Kaur
PurposeThe current study aims to predict consumer complaint status (complainers or non-complainers) based on socio-demographic and psychographic factors and further to discern the differences in behavior disposition of consumer groups concerning determinants of consumer's tendency to exit (TE).Design/methodology/approachThe research used survey-based data of 600 Indian consumers of three service sectors (hotel and hospitality, automobile service centers and organized retail stores). Chi-square automatic interaction detector (CHAID) decision tree analysis was used to profile consumers.FindingsThe results indicated that occupation; income; education; industry and attitude toward complaining were significant factors in profiling consumers as complainers or non-complainers. Further, determinants of TE (discouraging subjective norms, perceived likelihood of successful complaint, lower perceived switching cost, poor employee response, negative past experience and ease of complaint process) vary significantly across the groups of complainers and non-complainers.Research limitations/implicationsThe research questions in this study were tested with three service sectors consumers in India, so due care should be exercised in generalizing these findings to other sectors and countries. Study replication across other service sectors and countries is recommended to improve the generalizability of these findings with wider socio-demographic samples.Practical implicationsFirms striving for consumer retention and aim to extend their consumer life cycle can greatly benefit from the results of this study to understand the customer complaint behavior (CCB) specific to non-complaining (exit) behavior. The future researcher may benefit from replicating and extending the model in different industries for further contribution to the CCB literature.Originality/valueTo the best of the author's knowledge, there is no evidence of consumer segmentation based on their complaining behavior or socio-demographic and psychographic factors by employing CHAID decision tree analysis. In addition to illustrating the use of data mining techniques such as CHAID in the field of CCB, it also contributes to the extant literature by researching in a non-Western setting like India.
{"title":"Predicting complaint voicing or exit amidst Indian consumers: a CHAID analysis","authors":"Ami A. Kumar, Anupriya Kaur","doi":"10.1108/jamr-03-2022-0054","DOIUrl":"https://doi.org/10.1108/jamr-03-2022-0054","url":null,"abstract":"PurposeThe current study aims to predict consumer complaint status (complainers or non-complainers) based on socio-demographic and psychographic factors and further to discern the differences in behavior disposition of consumer groups concerning determinants of consumer's tendency to exit (TE).Design/methodology/approachThe research used survey-based data of 600 Indian consumers of three service sectors (hotel and hospitality, automobile service centers and organized retail stores). Chi-square automatic interaction detector (CHAID) decision tree analysis was used to profile consumers.FindingsThe results indicated that occupation; income; education; industry and attitude toward complaining were significant factors in profiling consumers as complainers or non-complainers. Further, determinants of TE (discouraging subjective norms, perceived likelihood of successful complaint, lower perceived switching cost, poor employee response, negative past experience and ease of complaint process) vary significantly across the groups of complainers and non-complainers.Research limitations/implicationsThe research questions in this study were tested with three service sectors consumers in India, so due care should be exercised in generalizing these findings to other sectors and countries. Study replication across other service sectors and countries is recommended to improve the generalizability of these findings with wider socio-demographic samples.Practical implicationsFirms striving for consumer retention and aim to extend their consumer life cycle can greatly benefit from the results of this study to understand the customer complaint behavior (CCB) specific to non-complaining (exit) behavior. The future researcher may benefit from replicating and extending the model in different industries for further contribution to the CCB literature.Originality/valueTo the best of the author's knowledge, there is no evidence of consumer segmentation based on their complaining behavior or socio-demographic and psychographic factors by employing CHAID decision tree analysis. In addition to illustrating the use of data mining techniques such as CHAID in the field of CCB, it also contributes to the extant literature by researching in a non-Western setting like India.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49249197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-23DOI: 10.1108/jamr-07-2021-0242
K. Pandey, D. Shukla
PurposeThe K-means (KM) clustering algorithm is extremely responsive to the selection of initial centroids since the initial centroid of clusters determines computational effectiveness, efficiency and local optima issues. Numerous initialization strategies are to overcome these problems through the random and deterministic selection of initial centroids. The random initialization strategy suffers from local optimization issues with the worst clustering performance, while the deterministic initialization strategy achieves high computational cost. Big data clustering aims to reduce computation costs and improve cluster efficiency. The objective of this study is to achieve a better initial centroid for big data clustering on business management data without using random and deterministic initialization that avoids local optima and improves clustering efficiency with effectiveness in terms of cluster quality, computation cost, data comparisons and iterations on a single machine.Design/methodology/approachThis study presents the Normal Distribution Probability Density (NDPD) algorithm for big data clustering on a single machine to solve business management-related clustering issues. The NDPDKM algorithm resolves the KM clustering problem by probability density of each data point. The NDPDKM algorithm first identifies the most probable density data points by using the mean and standard deviation of the datasets through normal probability density. Thereafter, the NDPDKM determines K initial centroid by using sorting and linear systematic sampling heuristics.FindingsThe performance of the proposed algorithm is compared with KM, KM++, Var-Part, Murat-KM, Mean-KM and Sort-KM algorithms through Davies Bouldin score, Silhouette coefficient, SD Validity, S_Dbw Validity, Number of Iterations and CPU time validation indices on eight real business datasets. The experimental evaluation demonstrates that the NDPDKM algorithm reduces iterations, local optima, computing costs, and improves cluster performance, effectiveness, efficiency with stable convergence as compared to other algorithms. The NDPDKM algorithm minimizes the average computing time up to 34.83%, 90.28%, 71.83%, 92.67%, 69.53% and 76.03%, and reduces the average iterations up to 40.32%, 44.06%, 32.02%, 62.78%, 19.07% and 36.74% with reference to KM, KM++, Var-Part, Murat-KM, Mean-KM and Sort-KM algorithms.Originality/valueThe KM algorithm is the most widely used partitional clustering approach in data mining techniques that extract hidden knowledge, patterns and trends for decision-making strategies in business data. Business analytics is one of the applications of big data clustering where KM clustering is useful for the various subcategories of business analytics such as customer segmentation analysis, employee salary and performance analysis, document searching, delivery optimization, discount and offer analysis, chaplain management, manufacturing analysis, productivity analysis, specialized emplo
{"title":"NDPD: an improved initial centroid method of partitional clustering for big data mining","authors":"K. Pandey, D. Shukla","doi":"10.1108/jamr-07-2021-0242","DOIUrl":"https://doi.org/10.1108/jamr-07-2021-0242","url":null,"abstract":"PurposeThe K-means (KM) clustering algorithm is extremely responsive to the selection of initial centroids since the initial centroid of clusters determines computational effectiveness, efficiency and local optima issues. Numerous initialization strategies are to overcome these problems through the random and deterministic selection of initial centroids. The random initialization strategy suffers from local optimization issues with the worst clustering performance, while the deterministic initialization strategy achieves high computational cost. Big data clustering aims to reduce computation costs and improve cluster efficiency. The objective of this study is to achieve a better initial centroid for big data clustering on business management data without using random and deterministic initialization that avoids local optima and improves clustering efficiency with effectiveness in terms of cluster quality, computation cost, data comparisons and iterations on a single machine.Design/methodology/approachThis study presents the Normal Distribution Probability Density (NDPD) algorithm for big data clustering on a single machine to solve business management-related clustering issues. The NDPDKM algorithm resolves the KM clustering problem by probability density of each data point. The NDPDKM algorithm first identifies the most probable density data points by using the mean and standard deviation of the datasets through normal probability density. Thereafter, the NDPDKM determines K initial centroid by using sorting and linear systematic sampling heuristics.FindingsThe performance of the proposed algorithm is compared with KM, KM++, Var-Part, Murat-KM, Mean-KM and Sort-KM algorithms through Davies Bouldin score, Silhouette coefficient, SD Validity, S_Dbw Validity, Number of Iterations and CPU time validation indices on eight real business datasets. The experimental evaluation demonstrates that the NDPDKM algorithm reduces iterations, local optima, computing costs, and improves cluster performance, effectiveness, efficiency with stable convergence as compared to other algorithms. The NDPDKM algorithm minimizes the average computing time up to 34.83%, 90.28%, 71.83%, 92.67%, 69.53% and 76.03%, and reduces the average iterations up to 40.32%, 44.06%, 32.02%, 62.78%, 19.07% and 36.74% with reference to KM, KM++, Var-Part, Murat-KM, Mean-KM and Sort-KM algorithms.Originality/valueThe KM algorithm is the most widely used partitional clustering approach in data mining techniques that extract hidden knowledge, patterns and trends for decision-making strategies in business data. Business analytics is one of the applications of big data clustering where KM clustering is useful for the various subcategories of business analytics such as customer segmentation analysis, employee salary and performance analysis, document searching, delivery optimization, discount and offer analysis, chaplain management, manufacturing analysis, productivity analysis, specialized emplo","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44799712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-23DOI: 10.1108/jamr-04-2022-0079
Junghun Han
PurposePrevious studies on employee turnover did not explore the contextual differences of emerging markets such as Vietnam. As Vietnam is a fast-growing new tiger economy with a high inflow of foreign direct investment, contextual analysis needs to be conducted to handle rising HR issues in the region. The current study aims to analyze paths to employee turnover intention through an integrated model covering factors on individual, team, and organizational levels to understand the contextual difference in the Vietnam F&B service industry.Design/methodology/approachA mixed method was used based on quantitative and qualitative data from three organizations. For the quantitative analysis, a path model was developed and analyzed by SEM-PLS (Smart PLS) based on a sample size of 354. For the qualitative analysis, 32 semi-structured interviews were conducted to explore the contextual understanding in the regional context.FindingsAlthough the current study confirms that the paths among the three levels show the turnover factors developed in the previous study still applicable to the Vietnam context, the strengths and relationships among the team and individual levels imply that the Vietnamese context created a unique HRM environment forming different paths to reach employee turnover decisions.Originality/valueThe findings contributed to the literature on employee turnover by developing an integrated model of employee turnover encompassing the three levels, suggesting the different local contexts formed unique paths to employee turnover decisions.
{"title":"A contextual study of employee turnover intention in Vietnam F&B service sector: an integrative perspective","authors":"Junghun Han","doi":"10.1108/jamr-04-2022-0079","DOIUrl":"https://doi.org/10.1108/jamr-04-2022-0079","url":null,"abstract":"PurposePrevious studies on employee turnover did not explore the contextual differences of emerging markets such as Vietnam. As Vietnam is a fast-growing new tiger economy with a high inflow of foreign direct investment, contextual analysis needs to be conducted to handle rising HR issues in the region. The current study aims to analyze paths to employee turnover intention through an integrated model covering factors on individual, team, and organizational levels to understand the contextual difference in the Vietnam F&B service industry.Design/methodology/approachA mixed method was used based on quantitative and qualitative data from three organizations. For the quantitative analysis, a path model was developed and analyzed by SEM-PLS (Smart PLS) based on a sample size of 354. For the qualitative analysis, 32 semi-structured interviews were conducted to explore the contextual understanding in the regional context.FindingsAlthough the current study confirms that the paths among the three levels show the turnover factors developed in the previous study still applicable to the Vietnam context, the strengths and relationships among the team and individual levels imply that the Vietnamese context created a unique HRM environment forming different paths to reach employee turnover decisions.Originality/valueThe findings contributed to the literature on employee turnover by developing an integrated model of employee turnover encompassing the three levels, suggesting the different local contexts formed unique paths to employee turnover decisions.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42644292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-19DOI: 10.1108/jamr-09-2021-0298
D. Cavazos, Nathan Heller
PurposeThe current study seeks to contribute to current self-regulation research by first exploring the association between the cost of self-regulation and firm self-regulation. The mediating role of association membership and firm slack is additionally explored.Design/methodology/approachLongitudinal analysis of firm-initiated product recalls for 15 manufacturers in the USA automobile industry from 1966 to 2012 has several important findings regarding the motivations for firm self-regulation.FindingsThe influence of industry associations and firm absorbed slack both contribute to firm self-regulation.Originality/valueThe current study begins to address the importance of firm characteristics in predicting self-regulation activities. The bulk of existing research has examined self-regulation at the industry level as an activity performed as a result of the adoption of formalized industry sanctioned standards of practice. This research contributes to such work by examining firm proactivity in the absence of such formal standards.
{"title":"Examining firm self-regulation in the automobile industry: the role of situational factors, firm characteristics and association influence","authors":"D. Cavazos, Nathan Heller","doi":"10.1108/jamr-09-2021-0298","DOIUrl":"https://doi.org/10.1108/jamr-09-2021-0298","url":null,"abstract":"PurposeThe current study seeks to contribute to current self-regulation research by first exploring the association between the cost of self-regulation and firm self-regulation. The mediating role of association membership and firm slack is additionally explored.Design/methodology/approachLongitudinal analysis of firm-initiated product recalls for 15 manufacturers in the USA automobile industry from 1966 to 2012 has several important findings regarding the motivations for firm self-regulation.FindingsThe influence of industry associations and firm absorbed slack both contribute to firm self-regulation.Originality/valueThe current study begins to address the importance of firm characteristics in predicting self-regulation activities. The bulk of existing research has examined self-regulation at the industry level as an activity performed as a result of the adoption of formalized industry sanctioned standards of practice. This research contributes to such work by examining firm proactivity in the absence of such formal standards.","PeriodicalId":46158,"journal":{"name":"Journal of Advances in Management Research","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45452384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}