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Industrial Management & Data Systems
Number of Followers: 7  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0263-5577
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  • Investigating the influence of organizational factors on blockchain
           adoption
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Blockchain possesses the potential to disrupt and reshape a plethora of industries in the next decade. However, blockchain adoption rates in technology developed countries, such as Ireland, are relatively low. Motivated by blockchain’s potential to transform sociotechnical systems, the lack of systematic inquiry pertaining to blockchain studies from an information system perspective, the authors propose the following research question: “How do organizational factors influence blockchain adoption in organizations based in a developed country'” Specifically, the purpose of this paper is to elucidate the impact of organizational factors on the adoption of blockchain and the adoption of blockchain in companies based in Ireland. Design/methodology/approach A comprehensive literature review was conducted, and the methods of qualitative content analysis were used to identify the most important technology–organization–environment (TOE) blockchain adoption factors. Organizational factors are often viewed as the most significant determinants of IT innovation adoption in organizations. Consequently, using a multiple-case study of 20 companies based in Ireland, the authors investigate how the top three organizational factors identified from the blockchain literature affected these companies decision to adopt or not adopt blockchain. Findings The literature review on blockchain adoption identified specific technological, organizational and environmental factors. Furthermore, the case study findings identified three patterns: top management support and organizational readiness are enablers for blockchain adoption, and large companies are more likely to adopt blockchain than small to medium-sized enterprises (SMEs). The authors explain these patterns by examining the nature of blockchain and the characteristics of Ireland as a developed country. Practical and scientific contributions are also presented. Research limitations/implications This study makes several important scientific contributions. First, the findings revealed that top management support and organizational readiness are significant enablers of blockchain adoption. Ireland is recognized as a technology developed country; however, the findings in relation to top management support contradict existing IT adoption literature pertaining to developed countries. Second, previous IT innovation adoption literature suggests that organizations size has a positive influence on a company’s IT innovation adoption process. This study demonstrates that large organizations are more likely to not only adopt blockchain but are also more likely to conduct increased levels of blockchain research and development activities. Finally, and most significantly, the authors identified several patterns, which relate specifically to Ireland as a developed country that influenced the findings. These findings could hold particular relevance to governments and organizations of other developed countries in terms of accelerating blockchain adoption. Practical implications The findings about the low level of blockchain awareness and the lack of information pertaining to viable business use cases indicate that the Irish government could play a more significant role in promoting the benefits of blockchain technologies. Further, the findings could also encourage IT providers to formulate enhanced strategies aimed at disseminating information pertaining to blockchain technologies. Second, the positive influence of top management support and organizational readiness, particularly about core competencies, on blockchain adoption suggests that equipping managers with the requisite knowledge and skills will be crucial in adopting these IT innovations. Finally, organizations who adopted blockchain used cloud-based blockchain platforms and tools to overcome the constraints of their initial low levels of organizational readiness. Originality/value This is one of the first studies to identify specific TOE blockchain adoption factors. Further, the authors examine how the three most identified organizational adoption factors impact organizations decisions to adopt blockchain. Finally, the authors discuss how the resulting three patterns identified by examining the nature of blockchain and the characteristics of Ireland as a technology developed country.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-27T02:02:09Z
      DOI: 10.1108/IMDS-08-2018-0365
       
  • Human factors in information leakage: mitigation strategies for
           information sharing integrity
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to explore the human factors triggering information leakage and investigate how companies mitigate insider threat for information sharing integrity. Design/methodology/approach The methodology employed is multiple case studies approach with in-depth interviews with five multinational enterprises (MNEs)/multinational corporations (MNCs). Findings The findings reveal that information leakage can be approached with human governance mechanism such as organizational ethical climate and information security culture. Besides, higher frequency of leakages negatively affects information sharing integrity. Moreover, this paper also contributes to a research framework which could be a guide to overcome information leakage issue in information sharing. Research limitations/implications The current study involved MNCs/MNEs operating in Malaysia, while companies in other countries may have different ethical climate and information sharing culture. Thus, for future research, it will be good to replicate the study in a larger geographic region to verify the findings and insights of this research. Practical implications This research contributes to the industry and business that are striving toward solving the mounting problem of information leakage by raising awareness of human factors and to take appropriate mitigating governance strategies to pre-empt information leakage. This paper also contributes to a novel theoretical model that characterizes the iniquities of humans in sharing information, and suggests measures which could be a guide to avert disruptive leakages. Originality/value This paper is likely an unprecedented research in molding human governance in the domain of information sharing and its Achilles’ heel which is information leakage.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-27T02:00:49Z
      DOI: 10.1108/IMDS-12-2018-0546
       
  • The arithmetic complexity of online grocery shopping: the moderating role
           of product pictures
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Online grocery shopping possesses characteristics that can make it more difficult than regular online shopping. There are numerous buying decisions to make each shopping session, there are large ranges of product types to choose from and there is varied arithmetical complexity. The purpose of this paper is to examine how such characteristics influence the attitude of consumers toward online grocery shopping websites. Design/methodology/approach The authors hypothesized that the product type (search or experience product), the task arithmetic complexity, and the attention and cognitive load associated with browsing through product pictures have an effect on the attitude of online shoppers toward these websites. To test the hypotheses, 31 subjects participated in a within-subject laboratory experiment. Findings The results suggest that visual attention to product pictures has a positive effect on the attitude of online shoppers toward a website when they are shopping for experience goods, but that it has a negative effect on their attitude toward a website when the task arithmetic complexity is greater. They also suggest that the cognitive load associated with browsing through product pictures has a negative effect on the attitude of online shoppers toward a website when they are shopping for experience goods, and that greater cognitive load variation has a positive effect on their attitude toward a website when arithmetic task complexity is greater. Practical implications When designing online grocery websites, providing clear single unit quantities with pictures corresponding to the sales unit could help establish a clear baseline on which consumers can work out their quantity requirements. For decisions involving experience goods, product pictures may act as an important complementary information source and may even be more diagnostic than text description. Originality/value Results reinforce the relevance of enriching the study of self-reported measures of the user experience on e-commerce sites with automatic measures.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-26T09:38:44Z
      DOI: 10.1108/IMDS-04-2018-0151
       
  • An empirical analysis of rural farmers’ financing intention of
           inclusive finance in China
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to investigate and understand China’s rural farmers’ financing intention of inclusive finance, and it examines related drivers like knowledge of inclusive finance, perceived benefits and perceived risks of ordering finance. Besides, the social enterprise embeddedness and digital finance are integrated into the conceptual model to further investigate their moderating impact. Design/methodology/approach The authors designed an inclusive finance intention model to examine the relations between dependent variable knowledge of inclusive finance, intermediary variables perceived benefits and perceived risks of ordering finance and the independent variable financing intention of inclusive finance. The embeddedness of social enterprise and digital finance were identified as modifying factors. Both exploratory and conclusive research strategies were applied. A structured questionnaire was developed to collect empirical data from the rural areas of China. Findings It suggests that knowledge of inclusive finance can strengthen both perceived benefits and perceived risk of ordering finance. Interestingly, the embeddness of social enterprise can significantly reduce risk perceptions and improve perceived benefits of ordering finance. Furthermore, perceived benefits of ordering finance can positively enhance rural farmers’ financing intention of inclusive finance, whereas perceived risks can negatively influence the financing intention. Moreover, digital finance as a modifying factor can significantly strengthen the positive correlation between perceived benefits of ordering finance and financing intention of inclusive finance. Practical implications The research indicates that a systematic inclusive finance educational project is needed to enhance rural farmers’ understanding of inclusive finance and its components. Moreover, the study reveals that it is crucial to promote social enterprise participation and digital finance to develop inclusive finance in rural China, as the service attributes of social enterprise and efficiency of digital finance can greatly reduce the existing transaction cost of farmers. Originality/value The conceptual model would potentially contribute to researchers interested in investigating the financing intention of inclusive financial services relating to rural population. The integration of social enterprise embeddedness and digital finance is the uniqueness of this research conceptual model.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-26T08:55:42Z
      DOI: 10.1108/IMDS-08-2018-0374
       
  • Optimal eco-labeling strategy with imperfectly informed consumers
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to find the optimal environmental quality criteria for a strategic eco-labeling authority with three objectives (i.e. maximizing the aggregate environmental quality, maximizing the industry profit and maximizing the social welfare). Particularly, the authors investigate how the existence of imperfectly informed consumers affects labeling criteria determination and competition among firms. Design/methodology/approach A game-theoretic modeling approach was adopted in this paper. A three-stage sequential game was modeled and backward induction was used to solve for a subgame perfect Nash equilibrium. To investigate the impacts of the existence of imperfectly informed consumers, the equilibrium, if all consumers are perfectly informed of the eco-label, was studied as a benchmark. Findings A more strict eco-labeling criterion improves revenues for both the labeled and unlabeled firms. It is interesting to find that the eco-labeling criteria to maximize industry profits are stricter than the criteria to maximize social welfare. Moreover, when the fraction of imperfectly informed consumers increases, the eco-labeling criteria to maximize aggregate environmental quality or industry profits will be more strict, while the criteria to maximize the social welfare will be looser. Originality/value The authors analyze the equilibrium strategies for firms against the eco-labeling criteria certified by authority with different objectives. The obtained optimal labeling strategies could provide insightful guidelines for the certifying authority to select the best suitable labeling criteria to achieve its goals.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-26T08:45:43Z
      DOI: 10.1108/IMDS-06-2018-0256
       
  • The role of service providers in 3D printing adoption
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to identify challenges faced by industrial firms at different phases of adoption of 3D printing (3DP), and outline how 3DP service providers can help address these challenges. Design/methodology/approach Separate interview questionnaires for 3DP users and 3DP service providers were used to conduct semi-structured interviews. Findings The key 3DP adoption challenges are as follows: creating a business case; difficulty in using different materials; optimising the process for specific parts; lack of “plug and play” solutions offered by equipment manufacturers; limited availability of training and educational support; poor end product quality; machine breakdowns; and high cost of maintenance and spare components. Using the theoretical lens of the technology acceptance model, results show a lack of ease of use and technological turbulence impact companies’ decisions to adopt 3DP. 3DP service providers can indeed attempt to alleviate the above challenges faced by customers through providing multiple 3DP services across different stages of adoption. Research limitations/implications Future research should examine the role of 3DP equipment manufacturers and design and modeling software solutions providers in improving adoption and how 3DP equipment manufacturers could develop into more integrated service providers as the technology advances. Practical implications Service providers can help customers transition to 3DP and should develop a portfolio of services that fits different phases of adoption. Originality/value The paper outlines how 3DP service providers can help address customer challenges in adoption of 3DP across different stages of adoption.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-20T01:33:45Z
      DOI: 10.1108/IMDS-08-2018-0339
       
  • Throughput models for a dual-bay VLM order picking system under different
           configurations
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A dual-bay VLM order picking (dual-bay VLM-OP) system is a particular solution where the operator works in parallel with the crane, allowing higher throughput performance. The purpose of this paper is to define models for different operating configurations able to improve the total throughput of the dual-bay VLM-OP system. Design/methodology/approach Analytical models are developed to estimate the throughput of a dual-bay VLM-OP. A deep evaluation has been carried out, considering different storage assignment policies and the sequencing retrieval of trays. Findings A more accurate estimation of the throughput is demonstrated, compared to the application of previous models. Some use guidelines for practitioners and academics are derived from the analysis based on real data. Originality/value Differing from previous contributions, these models include the acceleration/deceleration of the crane and the probability of storage and retrieve of each single tray. This permits to apply these models to different storage assignment policies and to suggest when these policies can be profitably applied. They can also model the sequencing retrieval of trays.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-14T02:29:39Z
      DOI: 10.1108/IMDS-11-2018-0518
       
  • Activity scheduling and resource allocation with uncertainties and
           learning in activities
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to develop a model which schedules activities and allocates resources in a resource constrained project management problem. This paper also considers learning rate and uncertainties in the activity durations. Design/methodology/approach An activity schedule with requirements of different resource units is used to calculate the objectives: makespan and resource efficiency. A comparisons between non-dominated sorting genetic algorithm – II (NSGA-II) and non-dominated sorting genetic algorithm – III (NSGA-III) is done to calculate near optimal solutions. Buffers are introduced in the activity schedule to take uncertainty into account and learning rate is used to incorporate the learning effect. Findings The results show that NSGA-III gives better near optimal solutions than NSGA-II for multi-objective problem with different complexities of activity schedule. Research limitations/implications The paper does not considers activity sequencing with multiple activity relations (for instance partial overlapping among different activities) and dynamic events occurring in between or during activities. Practical implications The paper helps project managers in manufacturing industry to schedule the activities and allocate resources for a near-real world environment. Originality/value This paper takes into account both the learning rate and the uncertainties in the activity duration for a resource constrained project management problem. The uncertainty in both the individual durations of activities and the whole project duration time is taken into consideration. Genetic algorithms were used to solve the problem at hand.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:31:36Z
      DOI: 10.1108/IMDS-01-2019-0002
       
  • Artificial Intelligence in FinTech: understanding robo-advisors adoption
           among customers
    • Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Considering the increasing impact of Artificial Intelligence (AI) on financial technology (FinTech), the purpose of this paper is to propose a research framework to better understand robo-advisor adoption by a wide range of potential customers. It also predicts that personal and sociodemographic variables (familiarity with robots, age, gender and country) moderate the main relationships. Design/methodology/approach Data from a web survey of 765 North American, British and Portuguese potential users of robo-advisor services confirm the validity of the measurement scales and provide the input for structural equation modeling and multisample analyses of the hypotheses. Findings Consumers’ attitudes toward robo-advisors, together with mass media and interpersonal subjective norms, are found to be the key determinants of adoption. The influences of perceived usefulness and attitude are slightly higher for users with a higher level of familiarity with robots; in turn, subjective norms are significantly more relevant for users with a lower familiarity and for customers from Anglo-Saxon countries. Practical implications Banks and other firms in the finance industry should design robo-advisors to be used by a wide spectrum of consumers. Marketing tactics applied should consider the customer’s level of familiarity with robots. Originality/value This research identifies the key drivers of robo-advisor adoption and the moderating effect of personal and sociodemographic variables. It contributes to understanding consumers’ perceptions regarding the introduction of AI in FinTech.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:29:56Z
      DOI: 10.1108/IMDS-08-2018-0368
       
  • Perceived image study with online data from social media: the case of
           boutique hotels in China
    • First page: 950
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to deconstruct the multi-faceted dimensions of Chinese travellers’ image of boutique hotels with a large amount of online textual data from social media (53,427 reviews written from 2014 to 2018), reinforcing the value creation of user-generated content via social media. Design/methodology/approach With the aid of Python, a computer language, online textual reviews (53,427 reviews) of 86 high-end boutique hotels in seven cities (Beijing, Shanghai, Hangzhou, Nanjing, Chengdu, Qingdao and Sanya) were collected from the top-ranked online travel agency in China, Ctrip.com. Then, the overall perceived image of boutique hotels was revealed with the aid of Python. Findings The results showed multiple dimensions of the image of boutique hotels. The overall image can be grouped into eight dimensions (room, service, food, environment, entertainment, location, price and value, and uniqueness). An affective image based on eight dimensions was further developed in the Chinese boutique hotel context. It appears that online data from social media are beneficial for hotel managers to learn travellers’ overall perceptions of boutique hotels and help put more effective management strategies in place in the hospitality industry. Research limitations/implications The relationship between cognitive image and affective image should be further investigated in future research. Theoretical implications are discussed from both cognitive image and affective image perspectives in the boutique hotel context. Managerial implications are highlighted to help industry managers understand the travellers’ perceptions of the hotels, via online data from social media, and put more effective hotel strategies in hospitality industry. Originality/value By using textual online data from social media, this paper deconstructs both the cognitive image and the affective image of boutique hotels. The dimensions of the most frequently mentioned concepts related to the Chinese boutique hotel industry are profoundly deconstructed, as is the uniqueness of the image of boutique hotels. The work is valuable for promoting effective marketing strategies in the hotel industry.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-05-10T08:20:40Z
      DOI: 10.1108/IMDS-11-2018-0483
       
  • The impacts of time segment modeling in berth allocation and quay crane
           assignment on terminal efficiency
    • First page: 968
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to study the impacts of time segment modeling approach for berth allocation and quay crane (QC) assignment on container terminal operations efficiency. Design/methodology/approach The authors model the small time segment modeling approach, based on minutes, which can be a minute, 15 min, etc. Moreover, the authors divided the problem into three sub-problems and proposed a novel three-level genetic algorithm (3LGA) with QC shifting heuristics to deal with the problem. The objective function here is to minimize the total service time by using different time segments for comparison and analysis. Findings First, the study shows that by reducing the time segment, the complexity of the problem increases dramatically. Traditional meta-heuristic, such as genetic algorithm, simulated annealing, etc., becomes not very promising. Second, the proposed 3LGA with QC shifting heuristics outperforms the traditional ones. In addition, by using a smaller time segment, the idling time of berth and QC can be reduced significantly. This greatly benefits the container terminal operations efficiency, and customer service level. Practical implications Nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time, e.g. 1.5 h. Therefore, a traditional hourly based modeling approach may cause significant berth and QC idling, and consequently cannot meet their practical needs. In this connection, a small time segment modeling approach is requested by industrial practitioners. Originality/value In the existing literature, berth allocation and QC assignment are usually in an hourly based approach. However, such modeling induces much idling time and consequently causes low utilization and poor service quality level. Therefore, a novel small time segment modeling approach is proposed with a novel optimization algorithm.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-04-10T01:46:22Z
      DOI: 10.1108/IMDS-08-2018-0335
       
  • Category-based or piecemeal-based processing' A dual model of
           web-mobile service extension behavior
    • First page: 993
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The advancements of mobile technologies and devices have greatly facilitated the extension of online services from web to mobile environments. Drawing on the categorization theory, the purpose of this paper is to explore the impact of perceived entitativity on users’ web-mobile service extension behavior. The research model considers how perceived entitativity serves as a category cue to link the category- and piecemeal-based processing and shape users’ adoption of extended mobile services. Design/methodology/approach An online survey (n=552) was conducted to empirically test the model. The data were analyzed by structural equation modeling approach. Findings The results offer two major findings. First, performance expectancy, perceived controllability and subjective norm are important antecedents of users’ usage intention. Second, perceived entitativity has three types of effects on usage intention: it exerts a direct and positive influence on usage intention; it indirectly facilitates usage intention through increasing PE and perceived controllability; and it moderates the relationship between subjective norm and usage intention. Originality/value This study contributes to the literature by taking into account the interplay of category- and piecemeal-based processing to understand consumers’ web-mobile service extension behavior.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-04-10T01:49:03Z
      DOI: 10.1108/IMDS-04-2018-0184
       
  • Integrating theories to predict clothing purchase on SNS
    • First page: 1015
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to design and test a conceptual model integrating uses and gratifications (UGT), self-image congruity (SIC), and theory of planned behavior (TPB) theories to identify the drivers that lead users to develop intentions to purchase clothing products through social networking sites (SNS). Design/methodology/approach Using an online questionnaire, data were collected from customers of clothing products who visit the SNS of their preferred clothing brands (n=1,003). Empirical results, using partial least squares regressions, were used to test the conceptual model. Findings The results supported the model and showed, as the main result, that purchase intention through the use of SNS is positively affected by intentions to use SNS and SNS use. SNS use is influenced by intentions to use SNS and by UGT. Intentions to use SNS are positively affected by UGT, attitude and perceived behavioral control (PBC). Attitude is positively influenced by UGT, SIC, PBC and subjective norm. Social implications These findings reveal that the critical elements in achieving purchase intentions in users through SNS include obtaining their participation by managing the SNS according to users’ self-image and offering useful gratifications. Originality/value This paper integrates theories of SIC, UGT and the TPB in a context of technology post-adoption to understand users’ purchase intentions through SNS. By establishing this novel theoretical integration approach, this paper furthers insight into purchase intentions through SNS.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-05-16T10:12:06Z
      DOI: 10.1108/IMDS-10-2018-0430
       
  • The impacts of intra-organizational structural elements on supply chain
           integration
    • First page: 1031
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Following resource-based view, the purpose of this paper is to investigate the effects of three intra-organizational structural elements on supply chain integration (SCI). Design/methodology/approach Based on data collected from ten countries, this study employs the structural equation modeling method to test the proposed model. Findings The results demonstrate that teamwork culture is positively related to three dimensions of SCI. Organizational commitment has positive effects on internal and customer integration (CI), whereas it has no significant effect on supplier integration (SI). Human goodness is only positively related to internal integration, but has no significant effect on SI or CI. Originality/value This study contributes to both structural elements literature and SCI enabler literature by operationalizing three human-related components of structural elements and empirically investigating relationships between intra-organizational structural elements and SCI.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-05-10T08:25:00Z
      DOI: 10.1108/IMDS-08-2018-0353
       
  • Information sharing, coordination and supply chain performance
    • First page: 1046
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to explore the effects that customer structured and unstructured information sharing (IS) can have on customer operational and strategic coordination and on supply chain performance (SCP). In addition, the study examines how customer IS influences customer coordination under various levels of demand uncertainty (DU). Design/methodology/approach The conceptual model for this study is designed on the basis of information-processing theory (IPT). Using data collected from 622 manufacturers in mainland China and Taiwan, the theoretical model is tested using the structural equation modeling method. Findings The authors find that both customer structured IS and unstructured IS are positively associated with customer strategic coordination. Customer structured IS increases customer operational coordination, but customer unstructured IS does not. DU positively moderates the relations between customer unstructured IS and strategic coordination, and between customer structured IS and operational coordination. Also, DU negatively moderates the relationship between customer structured IS and strategic coordination. Customer strategic coordination is positively related to SCP and to operational coordination. Customer operational coordination has no significant impact on SCP. Originality/value This study deepens our understanding of customer IS by distinguishing between customer structured and unstructured IS. The study also provides a greater understanding of customer coordination by making a distinction between the customer strategic and the operational coordination. The findings extend the empirical application of IPT. In addition, this study’s findings direct SC managers to apply varied customer IS practices that can enhance specific kinds of customer coordination activities, thereby enabling improved SCP.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:23:54Z
      DOI: 10.1108/IMDS-10-2018-0453
       
  • Big data analytics – enabled cyber-physical system: model and
           applications
    • First page: 1072
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to propose a comprehensive framework for integrating big data analytics (BDA) into cyber-physical system (CPS) solutions. This framework provides a wide range of functions, including data collection, smart data preprocessing, smart data mining and smart data visualization. Design/methodology/approach The architecture of CPS was designed with cyber layer, physical layer and communication layer from the perspective of big data processing. The BDA model was integrated into a CPS that enables managers to make sound decisions. Findings The effectiveness of the proposed BDA model has been demonstrated by two practical cases − the prediction of energy output of the power grid and the estimate of the remaining useful life of the aero-engine. The method can be used to control the power supply system and help engineers to maintain or replace the aero-engine to maintain the safety of the aircraft. Originality/value The communication layer, which connects the cyber layer and physical layer, was designed in CPS. From the communication layer, the redundant raw data can be converted into smart data. All the necessary functions of data collection, data preprocessing, data storage, data mining and data visualization can be effectively integrated into the BDA model for CPS applications. These findings show that the proposed BDA model in CPS can be used in different environments and applications.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:16:54Z
      DOI: 10.1108/IMDS-10-2018-0445
       
  • Can search engine data improve accuracy of demand forecasting for new
           products' Evidence from automotive market
    • First page: 1089
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose The purpose of this paper is to analyze the relationship between new product diffusion and consumer internet search patterns using big data and to investigate whether such data can be used in forecasting new product diffusion. Design/methodology/approach This research proposes a new product diffusion model based on the Bass diffusion model by incorporating consumer internet search behavior. Actual data from search engine queries and new vehicle sales for each vehicle class and region are used to estimate the proposed model. Statistical analyses are used to interpret the estimated results, and the prediction performance of the proposed method is compared with other methods to validate the usefulness of data for internet search engine queries in forecasting new product diffusion. Findings The estimated coefficients of the proposed model provide a clear interpretation of the relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases, analyzing the internet search pattern data are significant to explain new product diffusion and that internet search volume helps to predict new product diffusion. Therefore, marketing that seeks to increase internet search volume could positively affect vehicle sales. In addition, the demand forecasting performance of the proposed diffusion model is superior to those of other models for both long-term and short-term predictions. Research limitations/implications As search queries have only been available since 2004, comparisons with data from earlier years are not possible. The proposed model can be extended using other big data from additional sources. Originality/value This research directly demonstrates the relationship between new product diffusion and consumer internet search pattern and investigates whether internet search queries can be used to forecast new product diffusion by product type and region. Based on the estimated results, increasing internet search volume could positively affect vehicle sales across product types and regions. Because the proposed model had the best prediction power compared with the other considered models for all cases with large margins, it can be successfully utilized in forecasting demand for new products.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-05-31T11:13:38Z
      DOI: 10.1108/IMDS-08-2018-0347
       
  • Examining the influential factors for continued social media use
    • First page: 1104
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Drawing upon the theory of planned behavior (TPB) and the self-regulation framework, the purpose of this paper is to investigate whether and how factors for social media continuance behaviors work differently between social networking sites and microblogging. Design/methodology/approach A survey method was used to collect two samples of 557 social networking sites users and 568 microblogging users. The proposed research model was tested with the structural equation modeling technique. Findings The empirical results demonstrate that the impacts of influencing factors on users’ continuance behaviors vary by types of social media services. Information sharing has a stronger impact on microblog users’ satisfaction than social network users while social interaction has a stronger impact on satisfaction for social network users than microblog users. In addition, interpersonal influence is more effective in shaping satisfaction for the social network users while media influence is more effective in shaping satisfaction for the microblog users. Originality/value This is one of the first studies that integrate TPB with Bagozzi’s self-regulation framework to understand the behavioral model of social networking and microblogging continuance. The findings show that the impacts of attitudinal beliefs regarding information sharing and social interaction on social media users’ satisfaction are different across social networking and microblogging contexts. Moreover, this study also reveals different effects of two specific subjective norms – interpersonal and media influence – on continued use of social networking and microblogging.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:26:14Z
      DOI: 10.1108/IMDS-05-2018-0221
       
  • Gender differentials and implicit feedback on online video content:
           enhancing user interest evaluation
    • First page: 1128
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Exponential growth in online video content makes viewing choice and video promotion increasingly challenging. While explicit recommendation systems have value, they inherently distract the user from normal behaviour and are open to numerous biases. To enhance user interest evaluation accuracy, the purpose of this paper is to comprehensively examine the relationship between implicit feedback and online video content, and reviews gender differentials in the interest indicated by a comprehensive set of viewer responses. Design/methodology/approach This paper includes 200 useable observations based on an experiment of user interaction with the Youku platform (one of the largest video-hosting websites in China). Logistic regression was employed for its simple interpretation to test the proposed hypotheses. Findings The findings demonstrate gender differentials in cursor movement behaviour, explainable via well-studied splits in personality, biological factors, primitive behaviour and emotion management. This work offers a solution to the sparsity of work on implicit feedback, contributing to the literature that combines explicit and implicit feedback. Practical implications This study offers a launch point for further work on human–computer interaction, and highlights the importance of looking beyond individual metrics to embrace wider human traits in video site design and implementation. Originality/value This paper links implicit feedback to online video content for the first time, and demonstrates its value as an interest capturing tool. By reviewing gender differentials in the interest indicated by a comprehensive set of viewer responses, this paper indicates how user characteristics remain critical. Consequently, this work signposts highly fruitful directions for both practitioners and researchers.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:25:14Z
      DOI: 10.1108/IMDS-12-2018-0551
       
  • Barriers of embedding big data solutions in smart factories: insights from
           SAP consultants
    • First page: 1147
      Abstract: Industrial Management & Data Systems, Ahead of Print.
      Purpose Big data is a key component to realise the vision of smart factories, but the implementation and usage of big data analytical tools in the smart factory context can be fraught with challenges and difficulties. The purpose of this paper is to identify potential barriers that hinder organisations from applying big data solutions in their smart factory initiatives, as well as to explore causal relationships between these barriers. Design/methodology/approach The study followed an inductive and exploratory nature. Ten in-depth semi-structured interviews were conducted with a group of highly experienced SAP consultants and project managers. The qualitative data collected were then systematically analysed by using a thematic analysis approach. Findings A comprehensive set of barriers affecting the implementation of big data solutions in smart factories had been identified and divided into individual, organisational and technological categories. An empirical framework was also developed to highlight the emerged inter-relationships between these barriers. Originality/value This study built on and extended existing knowledge and theories on smart factory, big data and information systems research. Its findings can also raise awareness of business managers regarding the complexity and difficulties for embedding big data tools in smart factories, and so assist them in strategic planning and decision making.
      Citation: Industrial Management & Data Systems
      PubDate: 2019-06-07T01:28:15Z
      DOI: 10.1108/IMDS-11-2018-0532
       
 
 
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