Pub Date : 2023-01-01DOI: 10.1177/18479790231213556
Wang Xinhong, Zhu Dingju, Mo Yingxi
Regional culture plays an important role in the dissemination of culture along “the Belt and Road Initiative”, and through the efficient application, layout and flow of cultural resources, it can achieve industrial and economic efficiency. Cultural exchanges and interflow are raised and recommended by “the Belt and Road Initiative”. From the three dimensions of history, reality and development, the paradigm shift of regional culture in the context of “the Belt and Road Initiative”cultural development must be based on a historical and developmental perspective, with heritage and innovation as the body, and contemporary values to reflect on the problems in cultural development, so as to achieve the integration of unity and pluralism, and to provide a strong impetus for the cultural development of “the Belt and Road Initiative”.
{"title":"Logical coupling and paradigm shift of regional cultures in terms of “the belt and road initiative” —— A case study of lingnan culture","authors":"Wang Xinhong, Zhu Dingju, Mo Yingxi","doi":"10.1177/18479790231213556","DOIUrl":"https://doi.org/10.1177/18479790231213556","url":null,"abstract":"Regional culture plays an important role in the dissemination of culture along “the Belt and Road Initiative”, and through the efficient application, layout and flow of cultural resources, it can achieve industrial and economic efficiency. Cultural exchanges and interflow are raised and recommended by “the Belt and Road Initiative”. From the three dimensions of history, reality and development, the paradigm shift of regional culture in the context of “the Belt and Road Initiative”cultural development must be based on a historical and developmental perspective, with heritage and innovation as the body, and contemporary values to reflect on the problems in cultural development, so as to achieve the integration of unity and pluralism, and to provide a strong impetus for the cultural development of “the Belt and Road Initiative”.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135759575","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 : 2023-01-01DOI: 10.1177/18479790231203107
Byung-Hak Leem
The study aimed to investigate the relationship between content, teaching, and LMS platform, and student achievement in online classes. To accomplish this, the study drew upon the transactional distance theory and the community of inquiry framework. Using log data from the LMS platform, the study analyzed the impact of student-faculty interaction, student-content interaction, and student-systems interaction on learning outcomes. The sample consisted of online classes offered in the Department of International Marketing at B University in Korea during the spring semester of 2022. The study specifically targeted classes with 40 or more students to ensure an adequate sample size. The researchers used parallelism tests to confirm the validity of the research model, followed by a goodness of fit test with an ordinal Logit model. The results indicated that all three factors of interaction (content, teaching, and platform) had a significant positive effect on learning outcomes, while student-Zoom interaction did not. The interaction between learners and content was found to be the most important predictor of learning achievement, suggesting that student engagement with course materials plays a crucial role in their academic success. The study’s findings have important implications for educators who are interested in improving online teaching and learning. The study recommends expanding the empirical analysis of the research model from the existing structural equation or multiple regression model to the ordinal logit model to provide a more comprehensive understanding of the impact of these factors on student achievement. Overall, the study highlights the importance of considering the complex interaction between content, teaching, and platform in designing and delivering effective online courses that promote student engagement and achievement.
{"title":"Impact of interactivity on learning outcome in online learning settings: Ordinal logit model","authors":"Byung-Hak Leem","doi":"10.1177/18479790231203107","DOIUrl":"https://doi.org/10.1177/18479790231203107","url":null,"abstract":"The study aimed to investigate the relationship between content, teaching, and LMS platform, and student achievement in online classes. To accomplish this, the study drew upon the transactional distance theory and the community of inquiry framework. Using log data from the LMS platform, the study analyzed the impact of student-faculty interaction, student-content interaction, and student-systems interaction on learning outcomes. The sample consisted of online classes offered in the Department of International Marketing at B University in Korea during the spring semester of 2022. The study specifically targeted classes with 40 or more students to ensure an adequate sample size. The researchers used parallelism tests to confirm the validity of the research model, followed by a goodness of fit test with an ordinal Logit model. The results indicated that all three factors of interaction (content, teaching, and platform) had a significant positive effect on learning outcomes, while student-Zoom interaction did not. The interaction between learners and content was found to be the most important predictor of learning achievement, suggesting that student engagement with course materials plays a crucial role in their academic success. The study’s findings have important implications for educators who are interested in improving online teaching and learning. The study recommends expanding the empirical analysis of the research model from the existing structural equation or multiple regression model to the ordinal logit model to provide a more comprehensive understanding of the impact of these factors on student achievement. Overall, the study highlights the importance of considering the complex interaction between content, teaching, and platform in designing and delivering effective online courses that promote student engagement and achievement.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135446470","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 : 2023-01-01DOI: 10.1177/18479790231200614
Khai Loon Lee, Sze Yun Wong, Haitham M. Alzoubi, Barween Al Kurdi, Muhammad Turki Alshurideh, Mounir El Khatib
The manufacturing industry plays a crucial role in the economy of many countries, but there is a lack of expertise in implementing smart supply chains and smart technologies. This study aims to investigate the relationship between smart supply chains, smart technologies, and operational performance in the manufacturing industry. A survey questionnaire was conducted among registered manufacturing industries, and the results were analyzed using Smart PLS to test 10 hypotheses. Four hypotheses were supported out of 119 responses received through simple random sampling. The study suggests implementing instrumented supply chains using smart technologies can enhance operational performance. The findings provide valuable insights for policymakers, academics, and industry practitioners to improve the competitiveness of the manufacturing industry. This research emphasizes the importance of smart supply chains and smart technologies in achieving operational excellence, and further studies are necessary to address the identified limitations and contribute to a deeper understanding of the role of smart technologies in the supply chain’s digitalization.
{"title":"Adopting smart supply chain and smart technologies to improve operational performance in manufacturing industry","authors":"Khai Loon Lee, Sze Yun Wong, Haitham M. Alzoubi, Barween Al Kurdi, Muhammad Turki Alshurideh, Mounir El Khatib","doi":"10.1177/18479790231200614","DOIUrl":"https://doi.org/10.1177/18479790231200614","url":null,"abstract":"The manufacturing industry plays a crucial role in the economy of many countries, but there is a lack of expertise in implementing smart supply chains and smart technologies. This study aims to investigate the relationship between smart supply chains, smart technologies, and operational performance in the manufacturing industry. A survey questionnaire was conducted among registered manufacturing industries, and the results were analyzed using Smart PLS to test 10 hypotheses. Four hypotheses were supported out of 119 responses received through simple random sampling. The study suggests implementing instrumented supply chains using smart technologies can enhance operational performance. The findings provide valuable insights for policymakers, academics, and industry practitioners to improve the competitiveness of the manufacturing industry. This research emphasizes the importance of smart supply chains and smart technologies in achieving operational excellence, and further studies are necessary to address the identified limitations and contribute to a deeper understanding of the role of smart technologies in the supply chain’s digitalization.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135356707","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 : 2023-01-01DOI: 10.1177/18479790231176783
Saverio Ferraro, Alessandra Cantini, Leonardo Leoni, Filippo De Carlo
Organizations in today’s supply chains strive for transportation activities optimization. However, transportation is a significant environmental impact activity. Particularly, road transportation is the highest emission rate source and the most widespread modality for last-mile delivery. In this context, the use of performance management tools, such as key performance indicators (KPIs), is a strategy to reach both economic-operative and environmental benefits. Among all KPIs, overall equipment effectiveness (OEE) is one of the most suitable KPIs to measure the utilization of an industrial asset. In the transportation sector, a variant of the OEE, known as the transportation overall vehicle effectiveness (TOVE), is used to define the performance of vehicle distribution activities, such as road transportation for last-mile delivery and urban logistics. Although TOVE is effective for evaluating vehicle performance in terms of administrative availability, operating availability, performance, and quality, the indicator does not take into the environmental impact related to road transportation activities. Literature has proposed several formulations to quantify transport carbon emissions, most of which are linear relationships to the distance travelled. However, these models are not suitable for assessing the TOVE performance of road transportation activities. This paper aims to compare the performance of last-mile delivery in terms of TOVE and carbon emissions evaluated with a distance travelled formulation in two different scenario systems. The comparison shows the inadequacy of TOVE in terms of environmental sustainability, as maximizing road transport performance while ignoring the environmental dimension excludes the minimization of CO 2 emissions. Therefore, the foundation for future developments of TOVE for sustainable road transportation can be established from this divergence.
{"title":"Assessing the adequacy of transportation overall vehicle effectiveness for sustainable road transportation","authors":"Saverio Ferraro, Alessandra Cantini, Leonardo Leoni, Filippo De Carlo","doi":"10.1177/18479790231176783","DOIUrl":"https://doi.org/10.1177/18479790231176783","url":null,"abstract":"Organizations in today’s supply chains strive for transportation activities optimization. However, transportation is a significant environmental impact activity. Particularly, road transportation is the highest emission rate source and the most widespread modality for last-mile delivery. In this context, the use of performance management tools, such as key performance indicators (KPIs), is a strategy to reach both economic-operative and environmental benefits. Among all KPIs, overall equipment effectiveness (OEE) is one of the most suitable KPIs to measure the utilization of an industrial asset. In the transportation sector, a variant of the OEE, known as the transportation overall vehicle effectiveness (TOVE), is used to define the performance of vehicle distribution activities, such as road transportation for last-mile delivery and urban logistics. Although TOVE is effective for evaluating vehicle performance in terms of administrative availability, operating availability, performance, and quality, the indicator does not take into the environmental impact related to road transportation activities. Literature has proposed several formulations to quantify transport carbon emissions, most of which are linear relationships to the distance travelled. However, these models are not suitable for assessing the TOVE performance of road transportation activities. This paper aims to compare the performance of last-mile delivery in terms of TOVE and carbon emissions evaluated with a distance travelled formulation in two different scenario systems. The comparison shows the inadequacy of TOVE in terms of environmental sustainability, as maximizing road transport performance while ignoring the environmental dimension excludes the minimization of CO 2 emissions. Therefore, the foundation for future developments of TOVE for sustainable road transportation can be established from this divergence.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135840787","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 : 2023-01-01DOI: 10.1177/18479790221147864
S. Panigrahi, Khaloud Khalfan Al Ghafri, Wafa Rashid Al Alyani, Muhammad Waris Ali Khan, Taufiq Al Madhagy, Asadullah Khan
The main objective of the study is to empirically investigate the influence of lean manufacturing (LM) practices on the operational and business performance of manufacturing companies in Oman. Empirical data on LM practices and performance were collected using a self-administered structured survey questionnaire and the sampling frame was manufacturing companies in Oman. In total 300 questionnaires were distributed among 185 companies and a total of 107 with a response rate of 35.6 percent. The statistical analysis obtained from structural equation modeling found that lean manufacturing practices can explain operational performance, however, were unable to benefit overall business performance. Out of eight LM practices considered, small-lot production and quick setups were found to be the most adopted practices in manufacturing companies. Even though LM has become a fundamental aspect of industrial manufacturing processes; little is known about its impact on performance. This study adds value to the literature by examining the key LM practices-performance relationships within the manufacturing companies in Oman. These findings have significant implications for improving manufacturing organizations' operational and business performance through lean manufacturing strategies.
{"title":"Lean manufacturing practices for operational and business performance: A PLS-SEM modeling analysis","authors":"S. Panigrahi, Khaloud Khalfan Al Ghafri, Wafa Rashid Al Alyani, Muhammad Waris Ali Khan, Taufiq Al Madhagy, Asadullah Khan","doi":"10.1177/18479790221147864","DOIUrl":"https://doi.org/10.1177/18479790221147864","url":null,"abstract":"The main objective of the study is to empirically investigate the influence of lean manufacturing (LM) practices on the operational and business performance of manufacturing companies in Oman. Empirical data on LM practices and performance were collected using a self-administered structured survey questionnaire and the sampling frame was manufacturing companies in Oman. In total 300 questionnaires were distributed among 185 companies and a total of 107 with a response rate of 35.6 percent. The statistical analysis obtained from structural equation modeling found that lean manufacturing practices can explain operational performance, however, were unable to benefit overall business performance. Out of eight LM practices considered, small-lot production and quick setups were found to be the most adopted practices in manufacturing companies. Even though LM has become a fundamental aspect of industrial manufacturing processes; little is known about its impact on performance. This study adds value to the literature by examining the key LM practices-performance relationships within the manufacturing companies in Oman. These findings have significant implications for improving manufacturing organizations' operational and business performance through lean manufacturing strategies.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"183 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74625130","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 : 2023-01-01DOI: 10.1177/18479790231165639
Chris Y. T. Ma, D. Mo
Businesses are expected by the society to operate sustainably nowadays. However, companies are having a hard time to make business decisions to achieve both business sustainability and environmental sustainability, especially when such decisions involve numerous uncertainties. Making the wrong decision can result in damaging reputation in the least and going out of business in the worst. In this case study, we consider companies providing service parts maintenance, which have a great potential to bring positive impacts to the environment by refurbishing and reusing the replaced items. However, these companies also need to weight against cost effectiveness of doing so to maintain business sustainability. Informed decision making, meanwhile, is achievable with the use of the latest technologies. Here, we present the integration of Internet-of-Things to collect and provide real-time data for business analysis, such that companies can decide effectively which item(s) can be refurbished economically. We show that by doing so, uncertainties concerning the cost of refurbishment can be reduced, such that service parts operators can achieve both business sustainability and environmental sustainability.
{"title":"Integrating internet of things in service parts operations for sustainability","authors":"Chris Y. T. Ma, D. Mo","doi":"10.1177/18479790231165639","DOIUrl":"https://doi.org/10.1177/18479790231165639","url":null,"abstract":"Businesses are expected by the society to operate sustainably nowadays. However, companies are having a hard time to make business decisions to achieve both business sustainability and environmental sustainability, especially when such decisions involve numerous uncertainties. Making the wrong decision can result in damaging reputation in the least and going out of business in the worst. In this case study, we consider companies providing service parts maintenance, which have a great potential to bring positive impacts to the environment by refurbishing and reusing the replaced items. However, these companies also need to weight against cost effectiveness of doing so to maintain business sustainability. Informed decision making, meanwhile, is achievable with the use of the latest technologies. Here, we present the integration of Internet-of-Things to collect and provide real-time data for business analysis, such that companies can decide effectively which item(s) can be refurbished economically. We show that by doing so, uncertainties concerning the cost of refurbishment can be reduced, such that service parts operators can achieve both business sustainability and environmental sustainability.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"45 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91245447","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 : 2023-01-01DOI: 10.1177/18479790231151913
F. De Nicolò, L. Bellantuono, Dario Borzì, Matteo Bregonzio, Roberto Cilli, Leone De Marco, A. Lombardi, E. Pantaleo, L. Petruzzellis, Ariona Shashaj, S. Tangaro, A. Monaco, N. Amoroso, R. Bellotti
Online reviews have been found very useful in decision-making. It is important to design and implement accurate systems to analyze the reviews and, based on textual information, predict their ratings. Given the different sources, languages and evaluating systems, intelligent systems are needed to use textual and numerical reviews to better understand the evaluation of the tourist experience and derive useful information to improve the offer. This paper aims to present an eXplainable Artificial Intelligence framework that contributes to the discussion on numerical and textual evaluations of the hospitality experience. It combines sentiment analysis and machine learning to accurately model and explain the evaluation of the tourist experience. The main findings are that review ratings should be used with caution and accompanied by a sentiment evaluation and explainability plays a central role in identifying which are the key concepts of positive or negative ratings, providing invaluable intelligence about the tourist experience.
{"title":"The verbalization of numbers: An explainable framework for tourism online reviews","authors":"F. De Nicolò, L. Bellantuono, Dario Borzì, Matteo Bregonzio, Roberto Cilli, Leone De Marco, A. Lombardi, E. Pantaleo, L. Petruzzellis, Ariona Shashaj, S. Tangaro, A. Monaco, N. Amoroso, R. Bellotti","doi":"10.1177/18479790231151913","DOIUrl":"https://doi.org/10.1177/18479790231151913","url":null,"abstract":"Online reviews have been found very useful in decision-making. It is important to design and implement accurate systems to analyze the reviews and, based on textual information, predict their ratings. Given the different sources, languages and evaluating systems, intelligent systems are needed to use textual and numerical reviews to better understand the evaluation of the tourist experience and derive useful information to improve the offer. This paper aims to present an eXplainable Artificial Intelligence framework that contributes to the discussion on numerical and textual evaluations of the hospitality experience. It combines sentiment analysis and machine learning to accurately model and explain the evaluation of the tourist experience. The main findings are that review ratings should be used with caution and accompanied by a sentiment evaluation and explainability plays a central role in identifying which are the key concepts of positive or negative ratings, providing invaluable intelligence about the tourist experience.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"3 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85177552","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 : 2023-01-01DOI: 10.1177/18479790231186848
Lorenzo Polverino, R. Abbate, P. Manco, D. Perfetto, Francesco Caputo, R. Macchiaroli, M. Caterino
In the last decade, the adoption of technological tools in manufacturing industry, such as the use of the Internet of Things (IoT) and Machine Learning (ML), has led to the advent of the industry 4.0 (I4.0). In this scenario, intelligent devices can generate large volumes of data about industrial machinery and equipment that can be used to make maintenance more efficient. Prognostics and Health Management (PHM) is an emerging maintenance strategy that uses systems’ Condition Monitoring through IoT sensors installed on machinery to diagnose their faults or estimate their Remaining Useful Life (RUL). This study aims to conduct a Systematic Literature Review (SLR) on the use of ML techniques in the field of PHM of industrial mechanical systems and equipment. 50 studies resulted eligible for the above-mentioned SLR. Diagnostics and prognostics approach and the ML algorithm types used in the 50 analyzed papers have been analyzed together with the Key Performance Indicators (KPIs) used for their validation. From the analyses, it was found that Shallow Learning and Deep Learning (DL) algorithms are the most applied ones, while KPIs are used differently according to the type of task classification or regression. Moreover, results highlighted that many authors still use artificial datasets to test their algorithms, instead of datasets based on real data retrieved by their components. For the last type of datasets, this paper also introduces a schematic framework to standardize the step-by-step diagnostics and prognostics process carried out by the authors.
{"title":"Machine learning for prognostics and health management of industrial mechanical systems and equipment: A systematic literature review","authors":"Lorenzo Polverino, R. Abbate, P. Manco, D. Perfetto, Francesco Caputo, R. Macchiaroli, M. Caterino","doi":"10.1177/18479790231186848","DOIUrl":"https://doi.org/10.1177/18479790231186848","url":null,"abstract":"In the last decade, the adoption of technological tools in manufacturing industry, such as the use of the Internet of Things (IoT) and Machine Learning (ML), has led to the advent of the industry 4.0 (I4.0). In this scenario, intelligent devices can generate large volumes of data about industrial machinery and equipment that can be used to make maintenance more efficient. Prognostics and Health Management (PHM) is an emerging maintenance strategy that uses systems’ Condition Monitoring through IoT sensors installed on machinery to diagnose their faults or estimate their Remaining Useful Life (RUL). This study aims to conduct a Systematic Literature Review (SLR) on the use of ML techniques in the field of PHM of industrial mechanical systems and equipment. 50 studies resulted eligible for the above-mentioned SLR. Diagnostics and prognostics approach and the ML algorithm types used in the 50 analyzed papers have been analyzed together with the Key Performance Indicators (KPIs) used for their validation. From the analyses, it was found that Shallow Learning and Deep Learning (DL) algorithms are the most applied ones, while KPIs are used differently according to the type of task classification or regression. Moreover, results highlighted that many authors still use artificial datasets to test their algorithms, instead of datasets based on real data retrieved by their components. For the last type of datasets, this paper also introduces a schematic framework to standardize the step-by-step diagnostics and prognostics process carried out by the authors.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"18 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85357671","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 : 2023-01-01DOI: 10.1177/18479790231170962
K. P. Reddy, Venkateswarlu Chandu, Sambhana Srilakshmi, Elia Thagaram, Ch. Sahyaja, Bernard Osei
In today’s commercial world, ecological concerns have become increasingly essential. A lot of governments care about environmental issues. Sustainable development that doesn’t harm the environment is a major concern for companies today. The term “green marketing” describes the strategy of promoting and selling goods and services because of their positive impact on the natural world. Either the product or service itself is environmentally friendly, or the manufacturing process, packaging, and marketing are modified to be more eco-friendly. Concerns about how products harm the environment have recently been expressed by both manufacturers and consumers. Lead-free paint, organic foods, and low-power (or “energy-efficient”) electrical equipment are examples of products that consumers and manufacturers are focusing on as being “green” or ecologically friendly. Additionally, the importance of the green marketing idea is becoming more and more apparent to marketers. Though numerous green marketing studies have been conducted globally, there hasn’t been much academic research on consumer perception and preferences in India. This study explores consumer green ideals, environmental knowledge, green behaviours, and green products in addition to providing a brief review of environmental challenges. This article emphasises consumer views of and favorites for green marketing tactics and goods through the use of a planned questionnaire. To study was lead on 702 respondents. Customers demonstrated a high level of knowledge about eco marketing tactics and products. The respondents also showed strong environmental values. Research has offered helpful insights for green product marketers owing to the great perceived eco cost amongst customers, and it emphasises essential for creating marketing communication campaigns promoting green products.
{"title":"Consumers perception on green marketing towards eco-friendly fast moving consumer goods","authors":"K. P. Reddy, Venkateswarlu Chandu, Sambhana Srilakshmi, Elia Thagaram, Ch. Sahyaja, Bernard Osei","doi":"10.1177/18479790231170962","DOIUrl":"https://doi.org/10.1177/18479790231170962","url":null,"abstract":"In today’s commercial world, ecological concerns have become increasingly essential. A lot of governments care about environmental issues. Sustainable development that doesn’t harm the environment is a major concern for companies today. The term “green marketing” describes the strategy of promoting and selling goods and services because of their positive impact on the natural world. Either the product or service itself is environmentally friendly, or the manufacturing process, packaging, and marketing are modified to be more eco-friendly. Concerns about how products harm the environment have recently been expressed by both manufacturers and consumers. Lead-free paint, organic foods, and low-power (or “energy-efficient”) electrical equipment are examples of products that consumers and manufacturers are focusing on as being “green” or ecologically friendly. Additionally, the importance of the green marketing idea is becoming more and more apparent to marketers. Though numerous green marketing studies have been conducted globally, there hasn’t been much academic research on consumer perception and preferences in India. This study explores consumer green ideals, environmental knowledge, green behaviours, and green products in addition to providing a brief review of environmental challenges. This article emphasises consumer views of and favorites for green marketing tactics and goods through the use of a planned questionnaire. To study was lead on 702 respondents. Customers demonstrated a high level of knowledge about eco marketing tactics and products. The respondents also showed strong environmental values. Research has offered helpful insights for green product marketers owing to the great perceived eco cost amongst customers, and it emphasises essential for creating marketing communication campaigns promoting green products.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"124 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86900792","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 : 2023-01-01DOI: 10.1177/18479790231202420
Mohamed Basta, James Lapalme, Marc Paquet
Social responsibility issues keep reoccurring despite the popularity of numerous approaches perceived widely as adequate. In this paper, the authors conducted a systematic literature review to explore this phenomenon from a systems thinking standpoint. The findings revealed that each approach is founded on a different systemic paradigm, makes different assumptions on the nature of social responsibility issues, and has different objectives when resolving them. Therefore, employing any of these approaches alone will certainly fail given their underlying systemic limitations. The findings also revealed that these approaches are complementary from a critical systems thinking perspective, hence, researchers and practitioners can use their tools and methods together in the form of tailored interventions to better address efficiency, subjectivity, and fairness when resolving social responsibility issues. This paper concludes by proposing a practical framework based on critical systems practice which encompasses four systemic paradigms allowing the inclusion of a spectrum of perspectives, and assumptions.
{"title":"The systemic tenets of the key supply chain social responsibility approaches","authors":"Mohamed Basta, James Lapalme, Marc Paquet","doi":"10.1177/18479790231202420","DOIUrl":"https://doi.org/10.1177/18479790231202420","url":null,"abstract":"Social responsibility issues keep reoccurring despite the popularity of numerous approaches perceived widely as adequate. In this paper, the authors conducted a systematic literature review to explore this phenomenon from a systems thinking standpoint. The findings revealed that each approach is founded on a different systemic paradigm, makes different assumptions on the nature of social responsibility issues, and has different objectives when resolving them. Therefore, employing any of these approaches alone will certainly fail given their underlying systemic limitations. The findings also revealed that these approaches are complementary from a critical systems thinking perspective, hence, researchers and practitioners can use their tools and methods together in the form of tailored interventions to better address efficiency, subjectivity, and fairness when resolving social responsibility issues. This paper concludes by proposing a practical framework based on critical systems practice which encompasses four systemic paradigms allowing the inclusion of a spectrum of perspectives, and assumptions.","PeriodicalId":45882,"journal":{"name":"International Journal of Engineering Business Management","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135402685","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：