Pub Date : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739510
N. Handayani, Melissa Indah Fianty, N. Shabrina, K. Surendro
This study aims to determine the factors that influence employees' intentions to take certain actions or behaviors which have implications for employee satisfaction and employees' desires to leave the company. This research provides insights for companies so that they can utilize HR information systems (HRIS) not only for personnel administrative purposes but also for increasing company productivity. The results of this study are expected to provide the company an overview on how to automate human resources management by utilizing HRIS effectively and efficiently. The respondents of this research were HR employees who work in state-owned enterprises in Indonesia. Structural Equation Modeling was used to analyze the data and hypotheses. This study found that compatibility, visibility, and relative advantage have positive effects on behavioral intention to use and have implications for user satisfaction. In addition, this study also found a relationship between complexity and behavioral intention to use as well as between behavioral intention to use and turnover intention.
{"title":"Does Implementation of a Human Resource Information System Influence Employee's Turnover Intention in Developing Country?","authors":"N. Handayani, Melissa Indah Fianty, N. Shabrina, K. Surendro","doi":"10.1109/ICTMOD52902.2021.9739510","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739510","url":null,"abstract":"This study aims to determine the factors that influence employees' intentions to take certain actions or behaviors which have implications for employee satisfaction and employees' desires to leave the company. This research provides insights for companies so that they can utilize HR information systems (HRIS) not only for personnel administrative purposes but also for increasing company productivity. The results of this study are expected to provide the company an overview on how to automate human resources management by utilizing HRIS effectively and efficiently. The respondents of this research were HR employees who work in state-owned enterprises in Indonesia. Structural Equation Modeling was used to analyze the data and hypotheses. This study found that compatibility, visibility, and relative advantage have positive effects on behavioral intention to use and have implications for user satisfaction. In addition, this study also found a relationship between complexity and behavioral intention to use as well as between behavioral intention to use and turnover intention.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121058488","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739565
O. Saidi, Malek Masmoudi, Koffi Cobbold, Edgar Alfonso-Lizarazo, P. Albert
In this paper, we deal with transportation services' configuration in the context of centralization of sterilization service for a multi-hospital network. We address the problem as a Multi-trip VRP with pickup and delivery, with time windows and release dates. The objective is to design logistics trips between the network of hospitals and the sterilization center to pick-up contaminated reusable medical devices and distribute sterile ones while minimizing the transportation costs. We propose a mixed integer programming model and provide numerical experiments on randomly generated instances. A sensitivity analysis regarding several parameters is provided and the performance of the proposed model is shown.
{"title":"Optimizing transportation for a centralized sterilization service in a multi-hospital network","authors":"O. Saidi, Malek Masmoudi, Koffi Cobbold, Edgar Alfonso-Lizarazo, P. Albert","doi":"10.1109/ICTMOD52902.2021.9739565","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739565","url":null,"abstract":"In this paper, we deal with transportation services' configuration in the context of centralization of sterilization service for a multi-hospital network. We address the problem as a Multi-trip VRP with pickup and delivery, with time windows and release dates. The objective is to design logistics trips between the network of hospitals and the sterilization center to pick-up contaminated reusable medical devices and distribute sterile ones while minimizing the transportation costs. We propose a mixed integer programming model and provide numerical experiments on randomly generated instances. A sensitivity analysis regarding several parameters is provided and the performance of the proposed model is shown.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130173996","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 : 2021-11-24DOI: 10.1109/ictmod52902.2021.9739579
I. Mogul, Satya Shah
This research study aims to evaluate the significance of Technology and Industry 4.0 for Student Performance in Higher Education. Industry 4.0 is part of digital revolution which amalgamates various technologies like AI, distributed computing, virtual reality (VR), Internet of Things (IoT) & Big Data to bring a fundamental transformation in the current industry. The integration of these technologies has benefited all domains of society including Education. Education 4.0 aims to use Industry Revolution 4.0 technologies to the benefit of education field by providing means to improve the education sector using techniques like Education Mining, Prediction and Prescription of student's performance during their learning duration at universities. This study tries to highlight some important literature in the area of Industrial Revolution 4.0, Education 4.0, Big Data, Machine Learning, Descriptive, Predictive and Prescriptive analysis as well as learning analytics tools to provide a guidance for the stakeholders of the Education Industry to enrich their process for getting improved student performances at risk.
{"title":"Examine the impact of Technology and Industry 4.0 for Student Performance in Higher Education","authors":"I. Mogul, Satya Shah","doi":"10.1109/ictmod52902.2021.9739579","DOIUrl":"https://doi.org/10.1109/ictmod52902.2021.9739579","url":null,"abstract":"This research study aims to evaluate the significance of Technology and Industry 4.0 for Student Performance in Higher Education. Industry 4.0 is part of digital revolution which amalgamates various technologies like AI, distributed computing, virtual reality (VR), Internet of Things (IoT) & Big Data to bring a fundamental transformation in the current industry. The integration of these technologies has benefited all domains of society including Education. Education 4.0 aims to use Industry Revolution 4.0 technologies to the benefit of education field by providing means to improve the education sector using techniques like Education Mining, Prediction and Prescription of student's performance during their learning duration at universities. This study tries to highlight some important literature in the area of Industrial Revolution 4.0, Education 4.0, Big Data, Machine Learning, Descriptive, Predictive and Prescriptive analysis as well as learning analytics tools to provide a guidance for the stakeholders of the Education Industry to enrich their process for getting improved student performances at risk.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117310952","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739554
Jamel Gamra, Elaine Mosconi, Abdeslam Hassani
Adapting to the business environment and surviving in the digital economy requires businesses to innovate and rethink their strategy more often than before. This is complex for all organizations, but even more so for SMEs. Collaborative Innovation (CI) offers ways to overcome the scarcity of resources, typical in the context of SMEs. However, most of time CI requires strategic changes to adopt and integrate innovation. Literature suggests that Dynamic Capabilities (DC), which include sensing, seizing and resources reconfiguration capabilities, may help businesses in strategic changing. More, DC seem to support CI since the same capabilities are needed. Although both CI and DC have been well articulated in the literature, empirical evidence supporting their relationship is scarce. Our study contributes to reducing this gap by conducting an exploratory study based on a Systematic Literature Review. The objective of this paper is to explore the relationship between CI and DC.
{"title":"Collaborative Innovation and Dynamic Capabilities: A Systematic Literature Review","authors":"Jamel Gamra, Elaine Mosconi, Abdeslam Hassani","doi":"10.1109/ICTMOD52902.2021.9739554","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739554","url":null,"abstract":"Adapting to the business environment and surviving in the digital economy requires businesses to innovate and rethink their strategy more often than before. This is complex for all organizations, but even more so for SMEs. Collaborative Innovation (CI) offers ways to overcome the scarcity of resources, typical in the context of SMEs. However, most of time CI requires strategic changes to adopt and integrate innovation. Literature suggests that Dynamic Capabilities (DC), which include sensing, seizing and resources reconfiguration capabilities, may help businesses in strategic changing. More, DC seem to support CI since the same capabilities are needed. Although both CI and DC have been well articulated in the literature, empirical evidence supporting their relationship is scarce. Our study contributes to reducing this gap by conducting an exploratory study based on a Systematic Literature Review. The objective of this paper is to explore the relationship between CI and DC.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132063045","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739498
Ivana Basljan, Naomi-Frida Munitic, N. Peric, V. Lešić
Forecasting of demands of perishable goods is cru-cial in planning production schedules to satisfy customer needs on time, and to lower the profit losses of over or under stocks. Collaboration with one of local the supermarket chains provided a reasonable foundation for this academic study to optimize the forecasting of deliveries of perishable goods for food supply chains. By carefully analyzing its logistics operations and real-time data of short-shelf life product deliveries, it is discovered that the current supply management of the stores is solely based on prior managerial experiences, taking into consideration the spoilage, stock-out rates, and holiday seasons. Sudden change in demand causes problems to managers who struggle with keeping up with unpredictable frequency, type, and quantity of goods delivered to a particular place from an assigned warehouse. The paper presents a methodology for reliable planning and scheduling of orders of perishable goods, enabling planners to construct delivery schedules having a low expected total cost. This study aims to implement artificial intelligence where the demand for perishable goods can be predicted a few days in advance, also capable to cope with sudden changes. For that, the Gated Recurrent Unit recurrent neural networks are providing 81.3% average accuracy for observed 10 delivery points. Accurate prediction of demand results in delivering fresher products, which translates into economic benefits in terms of a higher product price.
{"title":"Prediction of perishable goods deliveries by GRU neural networks for reduction of logistics costs","authors":"Ivana Basljan, Naomi-Frida Munitic, N. Peric, V. Lešić","doi":"10.1109/ICTMOD52902.2021.9739498","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739498","url":null,"abstract":"Forecasting of demands of perishable goods is cru-cial in planning production schedules to satisfy customer needs on time, and to lower the profit losses of over or under stocks. Collaboration with one of local the supermarket chains provided a reasonable foundation for this academic study to optimize the forecasting of deliveries of perishable goods for food supply chains. By carefully analyzing its logistics operations and real-time data of short-shelf life product deliveries, it is discovered that the current supply management of the stores is solely based on prior managerial experiences, taking into consideration the spoilage, stock-out rates, and holiday seasons. Sudden change in demand causes problems to managers who struggle with keeping up with unpredictable frequency, type, and quantity of goods delivered to a particular place from an assigned warehouse. The paper presents a methodology for reliable planning and scheduling of orders of perishable goods, enabling planners to construct delivery schedules having a low expected total cost. This study aims to implement artificial intelligence where the demand for perishable goods can be predicted a few days in advance, also capable to cope with sudden changes. For that, the Gated Recurrent Unit recurrent neural networks are providing 81.3% average accuracy for observed 10 delivery points. Accurate prediction of demand results in delivering fresher products, which translates into economic benefits in terms of a higher product price.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114843576","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739353
B. Sharma, Sunaina Kuknor
Due to the emergence of technology, smart homes will be the next big thing in India. The study adopted a Value-based Adoption Model (VAM) to predict the consumer intention to use smart homes services in India. We used three constructs to measure the sacrifices and benefits: privacy risk, Technicality, perceived fees, usefulness, social inclusion, and status symbol. The effect of perceived value on Intention to use smart homes was predicted. The construct adopted from the previous studies was used to develop a structured questionnaire. We sent an electronic questionnaire to 98 respondents who were mostly aware of the technology of smart homes. The empirical model was tested by multiple linear regression with the help of SPSS software. The study concluded that the usefulness, perceived fees, and status symbol determine the perceived value, and perceived value successfully determining the Intention to use smart home services.
{"title":"Smart Homes adoption in India – Value-based Adoption Approach","authors":"B. Sharma, Sunaina Kuknor","doi":"10.1109/ICTMOD52902.2021.9739353","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739353","url":null,"abstract":"Due to the emergence of technology, smart homes will be the next big thing in India. The study adopted a Value-based Adoption Model (VAM) to predict the consumer intention to use smart homes services in India. We used three constructs to measure the sacrifices and benefits: privacy risk, Technicality, perceived fees, usefulness, social inclusion, and status symbol. The effect of perceived value on Intention to use smart homes was predicted. The construct adopted from the previous studies was used to develop a structured questionnaire. We sent an electronic questionnaire to 98 respondents who were mostly aware of the technology of smart homes. The empirical model was tested by multiple linear regression with the help of SPSS software. The study concluded that the usefulness, perceived fees, and status symbol determine the perceived value, and perceived value successfully determining the Intention to use smart home services.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116969573","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739482
M. Nikolaidou, Sotiris Koukoumtzis, Ioannis Routis, C. Bardaki
When integrating technology in every-day activities, new challenges arise. IoT systems have made their way in everyday life, resulting in smart environments enabling humans to make decisions in a more knowledgeable fashion. As smart systems become more complex, the process of using them becomes knowledge-intensive. This type of processes heavily depend on knowledge and experience of humans, that may work in a highly automated environment. In 2016, Case Management Model and Notation (CMMN) was introduced as a standard for modeling and automating human-centric processes. However, existing CMMN execution platforms have not met the full potential of the standard yet. In the paper, we aim to evaluate CMMN execution capabilities based on the experience obtained using two popular, advanced CMMN execution platforms. The evaluation is performed in the context of a smart farming case study based on twenty-five requirements imposed by knowledge-intensive processes, already identified in the literature.
{"title":"Evaluating CMMN execution capabilities: An empirical assessment based on a Smart Farming case study","authors":"M. Nikolaidou, Sotiris Koukoumtzis, Ioannis Routis, C. Bardaki","doi":"10.1109/ICTMOD52902.2021.9739482","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739482","url":null,"abstract":"When integrating technology in every-day activities, new challenges arise. IoT systems have made their way in everyday life, resulting in smart environments enabling humans to make decisions in a more knowledgeable fashion. As smart systems become more complex, the process of using them becomes knowledge-intensive. This type of processes heavily depend on knowledge and experience of humans, that may work in a highly automated environment. In 2016, Case Management Model and Notation (CMMN) was introduced as a standard for modeling and automating human-centric processes. However, existing CMMN execution platforms have not met the full potential of the standard yet. In the paper, we aim to evaluate CMMN execution capabilities based on the experience obtained using two popular, advanced CMMN execution platforms. The evaluation is performed in the context of a smart farming case study based on twenty-five requirements imposed by knowledge-intensive processes, already identified in the literature.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129138200","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739531
T. Agrawal, J. Angelis, Jagruti Ramsing Thakur, M. Wiktorsson, Ravi Kalaiarasan
With the increased electrification of transportation, there is a growth in the number of electric vehicles (EV) in use, and hence also discarded EV batteries. It is critical to trace the batteries so that the policy of electrification does not lead to a negative impact on sustainability. To achieve the goals of circular economy, it is necessary to consider the sustainable extended life cycle strategies of reduce, reuse and recycle. Information gathering and sharing through the supply chain is the key driver for enabling the tracking and tracing of materials and services needed. Traceability indicators across the value chain may enable the creation of a comprehensive database that aids the circular economy goals. In this study, we discuss three different circular economy business models and identify the key traceability indicators for enabling circularity in the lithium-ion battery application in the automotive sector. Insights are used to develop a framework for viable EV battery circularity, capturing three key circular economy elements and four traceability characteristics for different circularity types.
{"title":"Enabling circularity of electric vehicle batteries - the need for appropriate traceability","authors":"T. Agrawal, J. Angelis, Jagruti Ramsing Thakur, M. Wiktorsson, Ravi Kalaiarasan","doi":"10.1109/ICTMOD52902.2021.9739531","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739531","url":null,"abstract":"With the increased electrification of transportation, there is a growth in the number of electric vehicles (EV) in use, and hence also discarded EV batteries. It is critical to trace the batteries so that the policy of electrification does not lead to a negative impact on sustainability. To achieve the goals of circular economy, it is necessary to consider the sustainable extended life cycle strategies of reduce, reuse and recycle. Information gathering and sharing through the supply chain is the key driver for enabling the tracking and tracing of materials and services needed. Traceability indicators across the value chain may enable the creation of a comprehensive database that aids the circular economy goals. In this study, we discuss three different circular economy business models and identify the key traceability indicators for enabling circularity in the lithium-ion battery application in the automotive sector. Insights are used to develop a framework for viable EV battery circularity, capturing three key circular economy elements and four traceability characteristics for different circularity types.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127616633","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739635
Patrick Hosein
In order to determine an appropriate auto insurance policy premium one needs to take into account the risk associated with the drivers and cars on the policy. The premium is then typically a combination of the administrative and other costs required to support this customer, the profit margin desired by the provider (which in turn depends on the competition) and finally on the expected claims to be made on this policy based on risk. Given multiple features of the policy (age and gender of drivers, value of car, etc.) one can potentially provide personalized insurance policies based specifically on these policy features. However, as the level of personalization increases, the quantity of data available for predicting individual claim rates (the average total claim value per year) decreases and hence the robustness of the estimate decreases. The optimal level of personalization will depend on the number of samples and attributes as well as factors such as the variance of the claim rate for different attributes and the variation of the claim rate across categories of each attribute. We formulate a mathematical model for this trade-off and demonstrate how one can obtain the optimal choice. We demonstrate using illustrative examples as well as with data from an automobile insurance company.
{"title":"On the Prediction of Automobile Insurance Claims: The Personalization versus Confidence Trade-off","authors":"Patrick Hosein","doi":"10.1109/ICTMOD52902.2021.9739635","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739635","url":null,"abstract":"In order to determine an appropriate auto insurance policy premium one needs to take into account the risk associated with the drivers and cars on the policy. The premium is then typically a combination of the administrative and other costs required to support this customer, the profit margin desired by the provider (which in turn depends on the competition) and finally on the expected claims to be made on this policy based on risk. Given multiple features of the policy (age and gender of drivers, value of car, etc.) one can potentially provide personalized insurance policies based specifically on these policy features. However, as the level of personalization increases, the quantity of data available for predicting individual claim rates (the average total claim value per year) decreases and hence the robustness of the estimate decreases. The optimal level of personalization will depend on the number of samples and attributes as well as factors such as the variance of the claim rate for different attributes and the variation of the claim rate across categories of each attribute. We formulate a mathematical model for this trade-off and demonstrate how one can obtain the optimal choice. We demonstrate using illustrative examples as well as with data from an automobile insurance company.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131067808","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 : 2021-11-24DOI: 10.1109/ICTMOD52902.2021.9739335
Chiara Ancillai, Federica Pascucci
Servitization and digitalization are profoundly shaping companies’ activities. However, firms face significant challenges in implementing advanced services as well as in capturing value from investments in digital technologies. This has drawn the interests of scholars on digital servitization as a business model innovation process to cope with such difficulties. Yet, the literature seems to lack empirical evidence on digital servitization. Moreover, while increasing attention has been paid to Internet of Things, other technologies have been neglected. Hence, the study aims at understanding the role of 3D technologies in enabling digital servitization by conducting an explorative case study within the fashion industry.
{"title":"3D Technology-Based Servitization: an Explorative Study of Business Model Innovation","authors":"Chiara Ancillai, Federica Pascucci","doi":"10.1109/ICTMOD52902.2021.9739335","DOIUrl":"https://doi.org/10.1109/ICTMOD52902.2021.9739335","url":null,"abstract":"Servitization and digitalization are profoundly shaping companies’ activities. However, firms face significant challenges in implementing advanced services as well as in capturing value from investments in digital technologies. This has drawn the interests of scholars on digital servitization as a business model innovation process to cope with such difficulties. Yet, the literature seems to lack empirical evidence on digital servitization. Moreover, while increasing attention has been paid to Internet of Things, other technologies have been neglected. Hence, the study aims at understanding the role of 3D technologies in enabling digital servitization by conducting an explorative case study within the fashion industry.","PeriodicalId":154817,"journal":{"name":"2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121171739","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}
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