Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to develop a novel intuitionistic fuzzy seasonality regression (IFSR) with particle swarm optimization (PSO) algorithms to accurately forecast air pollutions, which are typical seasonal time series data. Seasonal time series prediction is a critical topic, and some time series data contain uncertain or unpredictable factors. To handle such seasonal factors and uncertain forecasting seasonal time series data, the proposed IFSR with the PSO method effectively extends the intuitionistic fuzzy linear regression (IFLR). Design/methodology/approach The prediction model sets up IFLR with spreads unrestricted so as to correctly approach the trend of seasonal time series data when the decomposition method is used. PSO algorithms were simultaneously employed to select the parameters of the IFSR model. In this study, IFSR with the PSO method was first compared with fuzzy seasonality regression, providing evidence that the concept of the intuitionistic fuzzy set can improve performance in forecasting the daily concentration of carbon monoxide (CO). Furthermore, the risk management system also implemented is based on the forecasting results for decision-maker. Findings Seasonal autoregressive integrated moving average and deep belief network were then employed as comparative models for forecasting the daily concentration of CO. The empirical results of the proposed IFSR with PSO model revealed improved performance regarding forecasting accuracy, compared with the other methods. Originality/value This study presents IFSR with PSO to accurately forecast air pollutions. The proposed IFSR with PSO model can efficiently provide credible values of prediction for seasonal time series data in uncertain environments. Citation: Industrial Management & Data Systems PubDate: 2018-10-31T01:46:52Z DOI: 10.1108/IMDS-02-2018-0063
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Confirmations are applied in kit preparation for mixed-model assembly to promote quality, but research that explains the impact on time efficiency has been lacking. The purpose of this paper is to determine the extent to which the type of confirmation method relates to time-efficient kit preparation when order batching is applied. Design/methodology/approach An industrially relevant laboratory experiment is applied, simulating kit preparation with order batching for mixed-model assembly. The time efficiency is studied as associated with four confirmation methods – barcode ring scanner, button presses, voice commands and RFID-reading wristbands – when applied as pick-from and place-to confirmation. Furthermore, the paper also considers the quality outcome. Findings Efficiency is promoted by methods that minimise interrupting the picker’s motions when performing pick-from confirmations and with methods that allow each hand to place components and perform place-to confirmations simultaneously – here represented by button presses and RFID-reading wristbands. Moreover, combining various methods for the tasks of pick-from or place-to confirmation can benefit efficiency. Research limitations/implications Pickers at an early stage of the learning curve (one shift of training) were considered. Practical implications The findings promote the customised applications of picking information systems in industry. Social implications Combining various methods for the tasks of pick-from and place-to confirmation can provide more fitting applications that better align with the picker’s preferences. Originality/value Combinations of various methods when applied as either pick-from or place-to confirmation, or both, are studied. Citation: Industrial Management & Data Systems PubDate: 2018-10-26T01:29:04Z DOI: 10.1108/IMDS-07-2018-0287
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Although the wind power industry has been booming in China during the last decade, the development of wind turbine aftermarket service is still lagging behind, which seriously affects the operational efficiency of wind farms. If wind turbine manufacturers get involved in the aftermarket, the service pricing policy will impact the profits of both the manufacturer and the wind farm. Therefore, it is necessary to discuss an optimal service pricing strategy in the wind turbine aftermarket and design a method to improve electricity generation efficiency through service contract design. The paper aims to discuss these issues. Design/methodology/approach In order to decide the maintenance quantity and channel effort level, the authors design a normal Stackelberg game and an efficiency value-added revenue-sharing contract and discuss two kinds of revenue increment sharing models under situations, in which the supply chain’s leaders are the wind farm and the wind turbine manufacturer, respectively. Findings The results show that in either case, there exist optimal power generation revenue-sharing ratios that can maximize profit. At the same time, the authors outline an optimal service pricing policy, maintenance demand policy and channel service effort-level policy. The results summarize the influences of wind aftermarket services on wind farms’ and wind turbine manufacturers’ profit, which provides managerial insights into the process of manufacturing servitization. Practical implications The manufacturer’s channel effort level will influence the power generation increments very much, so the authors have developed a mechanism to stimulate the manufacturer improving the efficiency of aftermarket services. Originality/value Taking the power generation increment revenue as the profit increment function, the authors discuss the influence of service price on the profit increment of the wind farm and the wind turbine manufacturer and also consider the influence of service price on the wind farms maintenance quantity and wind turbine manufacturers channel effort level. Citation: Industrial Management & Data Systems PubDate: 2018-10-26T01:27:24Z DOI: 10.1108/IMDS-01-2018-0032
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to propose a methodology to analyze a large amount of unstructured textual data into categories of business environmental analysis frameworks. Design/methodology/approach This paper uses machine learning to classify a vast amount of unstructured textual data by category of business environmental analysis framework. Generally, it is difficult to produce high quality and massive training data for machine-learning-based system in terms of cost. Semi-supervised learning techniques are used to improve the classification performance. Additionally, the lack of feature problem that traditional classification systems have suffered is resolved by applying semantic features by utilizing word embedding, a new technique in text mining. Findings The proposed methodology can be used for various business environmental analyses and the system is fully automated in both the training and classifying phases. Semi-supervised learning can solve the problems with insufficient training data. The proposed semantic features can be helpful for improving traditional classification systems. Research limitations/implications This paper focuses on classifying sentences that contain the information of business environmental analysis in large amount of documents. However, the proposed methodology has a limitation on the advanced analyses which can directly help managers establish strategies, since it does not summarize the environmental variables that are implied in the classified sentences. Using the advanced summarization and recommendation techniques could extract the environmental variables among the sentences, and they can assist managers to establish effective strategies. Originality/value The feature selection technique developed in this paper has not been used in traditional systems for business and industry, so that the whole process can be fully automated. It also demonstrates practicality so that it can be applied to various business environmental analysis frameworks. In addition, the system is more economical than traditional systems because of semi-supervised learning, and can resolve the lack of feature problem that traditional systems suffer. This work is valuable for analyzing environmental factors and establishing strategies for companies. Citation: Industrial Management & Data Systems PubDate: 2018-10-25T10:40:15Z DOI: 10.1108/IMDS-07-2017-0317
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The online crowdsourcing has been widely applied in the practice. The purpose of this paper is to investigate the all-pay auction contest in crowdsourcing, wherein a seeker posts a task online and the solvers decide whether to participate in the contest and in what extent to spend efforts on their submissions. Design/methodology/approach The authors specifically consider two classic contest formats: simultaneous contest and sequential contest, depending on whether the solver can observe the prior solvers’ submissions before making her own effort investment decision or not. They derive both seeker’s and solver’s equilibrium decisions and payoffs under different contest formats, and show that they vary significantly according to the number and the average skill level of solvers. Findings The results show that a solver would always invest more on her submission under simultaneous contest than under sequential contest, as she cannot confirm how other solvers’ submissions would be. This subsequently intensifies the market competition and brings down a solver’s average payoff under simultaneous contest. Although the simultaneous contest gives rise to a higher expected highest quality of all submissions, it also requires the seeker to spend more search cost to identify the best submission. Therefore, when the number of solvers is high or the average skill level is low, the seeker prefers sequential contest to simultaneous contest. The results also show an analogous preference over two formats for the platform. Originality/value This paper investigates two formats of all-pay auction contest in crowdsourcing and evaluates them from the perspective of solvers, seekers and platforms, respectively. The research offers many interesting insights which do not only explain the incentive mechanisms for solvers under different contest formats, but also make meaningful contributions to the seeker’s or the platform’s adoption strategies between two alternative contest formats in crowdsourcing practice. Citation: Industrial Management & Data Systems PubDate: 2018-10-19T12:47:53Z DOI: 10.1108/IMDS-09-2017-0433
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Starting from industry 4.0 in Germany and followed by the New Strategy for American Innovation in the USA and the smartization strategy in Japan, developed countries are pushing nation-wide innovation strategies. Similarly, China is pursuing the Made in China 2025, and Korea announced the Manufacturing Industry Innovation 3.0 strategy. However, few researchers have identified the industrial structure that establishes the foundation of the 4th Industrial Revolution or have derived strengths and weaknesses to provide implications on policy formulation through quantitative comparison with developed countries. Therefore, the purpose of this paper is to analyze the spillover effect of the information and communication technology (ICT) industry (the foundation of the 4th Industrial Revolution) and machinery·equipment industry (the foundation of smart manufacturing through convergence with ICT industry). Design/methodology/approach This study examines the industrial spillover effects of the ICT industry and machinery·equipment industry in the USA, Germany, Japan, China and Korea by using the World Input–Output Table from 2000 to 2014. Findings The results showed that backward linkage effect of the ICT Industry are high in the order of Korea≑China>Japan>the USA≑Germany, and forward linkage effect of the ICT industry are high in the order of Japan ≑> the USA≑Korea ≑> China ≑> Germany. Backward linkage effects of the machinery·equipment industry are high in the order of China>Japan≑Korea>the USA>Germany, and forward linkage effects of the machinery·equipment industry are high in the order of China>Korea>Germany≑Japan≑the USA. Practical implications China and Korea encourage active government investment in ICT and machinery·equipment industries, especially the intentional convergence between ICT and machinery·equipment industries is expected be generate higher synergy. The “innovation in manufacturing” strategy in the USA that utilizes its strength in ICT services seems appropriate, whereas Germany needs to revitalize the ICT industry to strengthen its manufacturing industry. Japan’s strategy is to focus its ICT capabilities on robot sector. While the scope of innovation is limited, its synergy is worth expecting. Originality/value This study attempted to provide a theoretical approach to the determination of national policy strategies and provide practical implications for response to the impacts of the 4th Industrial Revolution, by comparing the inducement effects of ICT and machinery·equipment industries between major countries. Citation: Industrial Management & Data Systems PubDate: 2018-10-10T12:49:42Z DOI: 10.1108/IMDS-05-2018-0215
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to examine the impact of renewable energy on the power supply chain and to study whether the renewable generator or the power grid that purchases power from the power spot market is better when the actual generation of renewable energy is insufficient. The authors want to compare and analyze the different power supply chain operation modes and discuss the optimal mode selection for renewable energy generator and power grid in different situations. Design/methodology/approach This paper studies the grid-led price competition game in the power supply chain, in which the power grid as a leader decides the price of transmission and distribution, and generators determine the power grid price. The renewable energy power generator and the traditional energy power generator conduct a price competition game; on the other hand, the power grid and power generators conduct Stackelberg games. The authors analyze the power supply of single power generator and two power generators, respectively, and research on the situation that the renewable energy cannot be fully recharged when the actual power generation is insufficient. Findings The study finds that both renewable and traditional power grid prices decline as price sensitivity coefficient of demand and installed capacity of renewable energy generators increase. Power grid premium decreases as the price sensitivity coefficient of demand increases, but rises as the installed capacity of renewable energy generator increases. When there is a shortage of power, if the installed capacity of renewable energy is relatively small and price sensitivity coefficient of demand is relatively large, the grid purchases the power from power spot market and shares cost with renewable energy generators, leading to higher expected profits of the renewable energy generators. On the contrary, the renewable energy generators prefer to make up power shortage themselves. For the power grid, purchasing the power by the renewable energy generators when there is a power shortage can bring more utility to the power grid when the installed capacity of renewable energy is lower and the demand price sensitivity coefficient is higher. When the installed capacity of renewable energy is high and the price sensitivity coefficient of demand is moderate, or the installed capacity of renewable energy is moderate and the demand price sensitivity coefficient is high, a generator that simultaneously possesses two kinds of energy source will bring more utility to the power grid. If the installed capacity of renewable energy and the demand price sensitivity coefficient both are small or the installed capacity of renewable energy and the price sensitivity coefficient of demand both are large, the power grid prefers to purchase the power by itself when there is a power shortage. Practical implications The goal of our paper analysis is to explore the implications of the theoretical model and address the series of research questions regarding the impact of the renewable energy on the power supply chain. The results of this study have key implications for reality. This paper sheds light on the power supply chain operation mode selection, which can potentially be used for the renewable energy generators to choose their operating mode and can also help traditional energy generators and power grid enterprises maximize their utility. This paper also has some references for the government to formulate the corresponding renewable energy development policy. Originality/value This paper studies the power operation mode under the uncertainty of supply and demand, and compares the advantages and disadvantages of renewable energy generator that makes up the shortage or the power grid purchases the power from power spot market then shares cost with the renewable energy generator. This paper analyzes the power grid-led coordination problem in a power supply chain, compares and analyzes the price competition game model of single power generator and dual power generators, and compares the different risk preferences of power grid. Citation: Industrial Management & Data Systems PubDate: 2018-10-10T12:48:22Z DOI: 10.1108/IMDS-01-2018-0041
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose This paper studies green vehicle routing problems of cold chain logistics with the consideration of the full set of greenhouse gas (GHG) emissions and an optimization model of green vehicle routing for cold chain logistics (with an acronym of GVRPCCL) is developed. The purpose of this paper is to minimize the total costs, which include vehicle operating cost, quality loss cost, product freshness cost, penalty cost, energy cost and GHG emissions cost. In addition, this research also investigates the effect of changing the vehicle maximum load in relation to cost and GHG emissions. Design/methodology/approach This study develops a mathematical optimization model, considering the total cost and GHG emission. The standard particle swarm optimization and modified particle swarm optimization (MPSO), based on an intelligent optimization algorithm, are applied in this study to solve the routing problem of a real case. Findings The results of this study show the extend of the proposed MPSO performing better in achieving green-focussed vehicle routing and that considering the full set of GHG costs in the objective functions will reduce the total costs and environmental-diminishing emissions of GHG through the comparative analysis. The research outputs also evaluated the effect of different enterprises’ conditions (e.g. customers’ locations and demand patterns) for better distribution routes planning. Research limitations/implications There are some limitations in the proposed model. This study assumes that the vehicle is at a constant speed and it does not consider uncertainties, such as weather conditions and road conditions. Originality/value Prior studies, particularly in green cold chain logistics vehicle routing problem, are fairly limited. The prior works revolved around GHG emissions problem have not considered methane and nitrous oxides. This study takes into account the characteristics of cold chain logistics and the full set of GHGs. Citation: Industrial Management & Data Systems PubDate: 2018-10-08T09:17:30Z DOI: 10.1108/IMDS-07-2018-0314
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to investigate political influential spreaders in Twitter at the juncture before and after the Malaysian General Election in 2013 (MGE2013) for the purpose of understanding if the political sphere within Twitter reflects the intentions, popularity and influence of political figures in the year in which Malaysia has its first “social media election.” Design/methodology/approach A Big Data approach was used for acquiring a series of longitudinal data sets during the election period. The work differs from existing methods focusing on the general statistics of the number of followers, supporters, sentiment analysis, etc. A retweeting network has been extracted from tweets and retweets and has been mapped to a novel information flow and propagation network we developed. The authors conducted quantitative studies using k-shell decomposition, which enables the construction of a quantitative Twitter political propagation sphere where members posited at the core areas are more influential than those in the outer circles and periphery. Findings The authors conducted a comparative study of the influential members of Twitter political propagation sphere on the election day and the day after. The authors found that representatives of political parties which are located at the center of the propagation network are winners of the presidential election. This may indicate that influential power within Twitter is positively related to the final election results, at least in MGE2013. Furthermore, a number of non-politicians located at the center of the propagation network also significantly influenced the election. Research limitations/implications This research is based on a large electoral campaign in a specific election period, and within a predefined nation. While the result is significant and meaningful, more case studies are needed for generalized application for identifying potential winning candidates in future social-media fueled political elections. Practical implications The authors presented a simple yet effective model for identifying influential spreaders in the Twitter political sphere. The application of the authors’ approach yielded the conclusion that online “coreness” score has significant influence to the final offline electoral results. This presents great opportunities for applying the novel methodology in the upcoming Malaysian General Election in 2018. The discovery presented here can be used for understanding how different players of political parties engage themselves in the election game in Twitter. The approach can also be adopted as a factor of influence for offline electoral activities. The conception of a quantitative approach in electoral results greatly influenced by social media means that comparative studies could be made in future elections. Originality/value Existing works related to general elections of various nations have either bypassed or ignored the subtle links between online and offline influential propagations. The modeling of influence from social media using a longitudinal and multilayered approach is also rarely studied. This simple yet effective method provides a new perspective of practice for understanding how different players behave and mutually shape each other over time in the election game. Citation: Industrial Management & Data Systems PubDate: 2018-10-03T10:27:08Z DOI: 10.1108/IMDS-09-2017-0409
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to investigate the relationship between the chief data officer’s (CDO) presence and firm performance, and the moderating effect of firm size. Design/methodology/approach The performance data for 64 treatment firms with CDOs and 64 control firms without CDOs is collected from Compustat database. The Wilcoxon signed-rank test is used to analyze the performance differences between treatment firms and control firms. Hierarchical regression method is used to test the moderating effect of firm size. Findings The results indicate that the profit ratios of treatment firms are significantly improved after the appointment of CDOs, and the profit ratios of treatment firms are significantly higher than that of the control firms. For the cost ratios, the findings provide some empirical evidence revealing two of the cost ratios are lower and only one ratio is higher for the treatment firms after CDOs’ appointment. Firm size moderates the relationship between the CDO’s presence and firm performance indicator, ROS, in the same direction. Firm size has no moderating effect on relationships between CDO’s presence and other performance indicators. Practical implications The findings provide practical insights that will help managers to realize the importance of CDOs and their work. CDOs would bring some cost to the firms, but they would bring more profit to firms. In addition, if for large firms, the CDO’s presence would bring more ROS. Originality/value The study explores the relationship between the CDO’s presence and firm performance. It is the first attempt to explore the CDO’s presence and the cost performance in the specific time period, and the study is also the first attempt to analyze the moderating effect of the firm size on the relationship between the CDO’s presence and firm performance. Citation: Industrial Management & Data Systems PubDate: 2018-10-02T01:01:51Z DOI: 10.1108/IMDS-03-2018-0101
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to investigate the relationship between several aspects of store flyers design (presence of a institutional slogan, type of product (national brand (NB) or store brand (SB)) featured on the cover page, the size of the flyer, number of featured NBs, type of brand (NB vs SB) on promotion, and price difference between the most expensive (NB) and the cheapest SB) and the consumer’s perceived variety of the retailer’s assortment, as a dimension of its global image. Design/methodology/approach A mixed laboratory experiment that combined a between-subjects experimental design and inter-subject conjoint analysis was conducted. A fictitious flyer from a fictitious supermarket was created that included both real NBs and fictitious SBs. In total, 12 scenarios (i.e. flyers) were tested using a sample of 406 participants. Findings Analysis suggests that longer flyers have the greatest influence on consumers’ perceived variety of a retailer’s assortment; a greater number of NBs in a category influenced consumers’ perceptions positively, and featuring SBs on the cover enhanced perceived variety. If a retailer features SBs on a flyer’s cover, longer flyers are recommended, and shorter flyers are recommended if NBs are featured on the cover. A retailer should promote its own brand only if the most expensive NBs are featured with SBs. Research limitations/implications This study analyses a single aspect of consumers’ purchasing behaviors – variety of a retailer’s assortment. Future research should examine other variables related to consumers’ purchasing behaviors. This study uses an online context to test hypotheses, but many aspects of flyer design are physical. Future research should test current findings in offline contexts to compare results. Research should also explore moderation by consumer variables such as brand and store loyalty. Practical implications To researchers, the authors offer improved understanding of how a flyer’s design affects the first stage of purchasing. To practitioners, results offer better understanding of positive returns on investment of store flyers, and to retailers, results offer a guide to creating and organizing flyers. Originality/value This study is first to assess how a flyer’s design influences a dimension of store image. Unlike extant research that examines store flyers using econometric models at the aggregate level, this study uses a laboratory experiment that combines a between-subjects design with conjoint analysis. Citation: Industrial Management & Data Systems PubDate: 2018-09-24T02:04:35Z DOI: 10.1108/IMDS-04-2018-0149
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose With social exchange theory as a basis, the purpose of this paper is to seek a better understanding of advice processes in online travel communities, which offer crucial advice for travelers’ decisions. It also predicts that relational capital variables (commitment, reciprocity perceptions) moderate the main relationships. Design/methodology/approach Data from a web survey of 456 users of online travel communities affirm the scale’s validity and provide the input for structural equation modeling and multisample analyses of the hypotheses. Findings Higher levels of commitment reinforce the effect of following past advice on passive and active participation intentions. Users’ perceptions of reciprocity in the community strengthen the influence of following past advice on active participation. However, a high level of reciprocity causes users following past advice to reduce their intentions to continue following that advice. Practical implications Management tactics should specify active and passive participation in online travel communities. Specifically, to encourage the creation of high-quality new content, community managers should create interactive environments marked by high levels of reciprocity and commitment. Originality/value This research elucidates the role of relational capital variables in advice processes and advances understanding of online travel communities. Citation: Industrial Management & Data Systems PubDate: 2018-09-21T02:03:34Z DOI: 10.1108/IMDS-03-2018-0098
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to provide a better understanding of how post-adoption use of business intelligence system (BIS) affects firm performance. It develops and empirically tests a conceptual model for assessing the impact of BIS routine and innovative usage on firm performance the context of small and medium enterprises (SMEs). Design/methodology/approach Drawing on the data collected from 181 SMEs we analyzed how BIS usage influences firm performance using the PLS-SEM method. Findings The paper provides empirical insights about how BIS routine and innovative usage affect firm performance. Practical implications The results provide instrumental insights for managers and solution providers to help them understand the influence of various determinants to more effectively conclude the post-adoption process in SMEs. Originality/value This study represents important progress in the authors’ theoretical understanding of the role of BIS routine and innovative usage across different BIS partial impacts on firm performance dimensions. Citation: Industrial Management & Data Systems PubDate: 2018-09-21T01:50:43Z DOI: 10.1108/IMDS-02-2018-0085
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to identify electronic word-of-mouth (eWOM) customers from customer reviews. Thus, firms can precisely leverage eWOM customers to increase their product sales. Design/methodology/approach This research proposed a framework to analyze the content of consumer-generated product reviews. Specific algorithms were used to identify potential eWOM reviewers, and then an evaluation method was used to validate the relationship between product sales and the eWOM reviewers identified by the authors’ proposed method. Findings The results corroborate that online product reviews that are made by the eWOM customers identified by the authors’ proposed method are more related to product sales than customer reviews that are made by non-eWOM customers and that the predictive power of the reviews generated by eWOM customers are significantly higher than the reviews generated by non-eWOM customers. Research limitations/implications The proposed method is useful in the data set, which is based on one type of products. However, for other products, the validity must be tested. Previous eWOM customers may have no significant influence on product sales in the future. Therefore, the proposed method should be tested in the new market environment. Practical implications By combining the method with the previous customer segmentation method, a new framework of customer segmentation is proposed to help firms understand customers’ value specifically. Originality/value This study is the first to identify eWOM customers from online reviews and to evaluate the relationship between reviewers and product sales. Citation: Industrial Management & Data Systems PubDate: 2018-09-06T12:39:11Z DOI: 10.1108/IMDS-09-2017-0418
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to investigate how different logistics resources and resource patterns, such as logistics infrastructure, logistics location, logistics knowledge and logistics information, affect logistics capabilities and operational performance. Design/methodology/approach Based on data collected from 273 companies in China, this study examines impacts of individual logistics resource dimensions on resource integration capability, customer service capability and operational performance through contingency approach. Furthermore, three logistics resource patterns are identified and linked with resource integration capability and operational performance through configuration approach. Findings Contingency results show that different logistics resources have different impacts on resource integration capability and operational performance. Configuration results reveal that companies’ capabilities and operational performance vary for different logistics resource patterns: the high-uniform pattern has a better resource integration capability and operational performance than other patterns, while all logistics resource patterns have similar customer service capability levels. Research limitations/implications Future studies should examine other resource capabilities and performance indicators of companies and extend this study to other countries and regions. Originality/value This study contributes to the logistics resource literature through empirically investigating relationships among logistics resources, resource integration capability and operational performance using contingency approach, and through identifying different logistics resource patterns based on configuration approach. The findings extend the logistics resource literature, particularly on research of logistics parks in China. Citation: Industrial Management & Data Systems PubDate: 2018-09-05T10:47:30Z DOI: 10.1108/IMDS-01-2018-0024
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose There are particularly high fresh agricultural product (FAP) loss rates in actual supply chain operation and the development of FAPs e-commerce is hindered to some extent. The purpose of this paper is to achieve the coordination of three-layer FAP supply chain and maximize profit through the contracts among the supply chain members. Design/methodology/approach A three-layer FAP supply chain that consists of a fresh produce e-commerce enterprise, third-party logistics service provider (TPLSP) and community convenience store under e-commerce environment is considered. New game models are developed and optimal decisions in centralized and decentralized channel are characterized. Different contract coordination mechanisms are designed to improve the supply chain performance. Finally, computational studies are conducted. Findings The decentralized supply chain cannot be coordinated by a freshness-keeping cost-sharing contract, and it can be coordinated by a freshness-keeping cost-sharing and revenue-sharing contract. The optimal unit online selling price, unit logistics distribution price, fresh-keeping effort and unit self-collection service price can all be achieved. Practical implications The paper provides a practical guideline to managers in fresh produce industry in terms of how to cooperate with other supply chain members so as to maximize total profit and achieve Pareto improvement while also supply the freshest and safest produce to the target market under e-commerce environment. Originality/value Few studies have explored the coordination of three-layer FAP supply chain under e-commerce environment with TPLSP and community convenience store’s participation in decisions, especially considering that the market demand for FAPs is affected by freshness and unit online selling price. In this paper, all these scenarios are taken into account and corresponding mathematical models are developed. In particular, different contract coordination mechanisms are designed and examined simultaneously. Citation: Industrial Management & Data Systems PubDate: 2018-08-28T01:46:34Z DOI: 10.1108/IMDS-12-2017-0559
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing. Design/methodology/approach It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience. Findings The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics. Practical implications The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences. Originality/value This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service. Citation: Industrial Management & Data Systems PubDate: 2018-08-23T12:20:05Z DOI: 10.1108/IMDS-01-2018-0007
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose It is necessary to determine the processes affecting cloud computing service applications in supply chain management (SCM) systems in order to facilitate cloud computing service exchanges and transmission of data among supply chain members. The paper aims to discuss these issues. Design/methodology/approach Drawing on the elaboration likelihood model (ELM) and integrating the commitment trust theory, this paper develops a theoretical model using argument advantage and source credibility constructs to examine the relationships among perceived usefulness, attitude, trust and usage intention. Findings The results indicate that both the central route and the peripheral route of the ELM have a positive influence on perceived usefulness. The argument advantage has a strong influence on perceived usefulness as compared to source credibility while source credibility has a strong impact on trust. Furthermore, the perceived usefulness of cloud computing services plays a pivotal role in attitude and intention, whereas trust has a weak effect on usage intention. Originality/value The proposed model not only explores the argument that potential user evaluations of both the advantages of cloud computing services and source credibility influence their affective states, which in turn affect their usage intention, but it also examines the mediating factors that influence processes related to cloud SCM acceptance. Citation: Industrial Management & Data Systems PubDate: 2018-08-23T12:19:12Z DOI: 10.1108/IMDS-12-2017-0589
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to formulate a framework to construct a patient-specific risk score and therefore to classify these patients into various risk groups that can be used as a decision support mechanism by the medical decision makers to augment their decision-making process, allowing them to optimally use the limited resources available. Design/methodology/approach A conventional statistical model (logistic regression) and two machine learning-based (i.e. artificial neural networks (ANNs) and support vector machines) data mining models were employed by also using five-fold cross-validation in the classification phase. In order to overcome the data imbalance problem, random undersampling technique was utilized. After constructing the patient-specific risk score, k-means clustering algorithm was employed to group these patients into risk groups. Findings Results showed that the ANN model achieved the best results with an area under the curve score of 0.867, while the sensitivity and specificity were 0.715 and 0.892, respectively. Also, the construction of patient-specific risk scores offer useful insights to the medical experts, by helping them find a trade-off between risks, costs and resources. Originality/value The study contributes to the existing body of knowledge by constructing a framework that can be utilized to determine the risk level of the targeted patient, by employing data mining-based predictive approach. Citation: Industrial Management & Data Systems PubDate: 2018-08-23T12:16:32Z DOI: 10.1108/IMDS-12-2017-0579
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to understand how knowledge spillover and access in a supply chain network enhance the credit quality in supply chain finance (SCF) of small and medium enterprises (SMEs). Design/methodology/approach Drawing on network theory and a knowledge-based view (KBV) of SCF, this paper proposes a theoretical model and tests it using survey data from a sample of 248 SMEs in China. Findings The main finding is that both strong ties and dense ties within a supply chain network have positive effects on SMEs’ credit quality, and these effects are mediated by knowledge spillover and knowledge access. Interestingly, knowledge spillover is found to have a positive effect on knowledge access. Originality/value This paper is the first to investigate the relationship between supply chain network and supply chain financing from a KBV. The proposed model captures the complexity in the interaction among different attributes of supply chain networks (i.e. strong ties and dense ties), different aspects of knowledge transfer (i.e. knowledge spillover and knowledge access) and SMEs’ credit quality in SCF. The results not only show the importance of SMEs’ supply chain networks to SMEs’ credit quality but also contribute to the understanding of the KBV in SCF. Citation: Industrial Management & Data Systems PubDate: 2018-08-17T09:46:49Z DOI: 10.1108/IMDS-01-2018-0049
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to illustrate an original decision-support tool (DST) that aids 3PL managers to decide on the proper warehouse management system (WMS) customization. The aim of this tool is to address to the three main issues affecting such decision: the cost of the information sharing, the scarce visibility of the client’s data and the uncertainty of quantifying the return from investing into a WMS feature. Design/methodology/approach The tool behaves as a digital twin of a WMS. In addition, it incorporates a set of WMS’s features based both on heuristics and optimization techniques and uses simulation to perform what-if multi-scenario analyses of alternative management scenarios. In order to validate the effectiveness of the tool, its application to a real-world 3PL warehouse operating in the sector of biomedical products is illustrated. Findings The results of a simulation campaign along an observation horizon of ten months demonstrate how the tool supports the comparison of alternative scenarios with the as-is, thereby suggesting the most suitable WMS customization to adopt. Practical implications The tool supports 3PL managers in enhancing the efficiency of the operations and the fulfilling of the required service level, which is increasingly challenging given the large inventory mix and the variable clients portfolio that 3PLs have to manage. Particularly, the choice of the WMS customization that better perform with each business can be problematic, given the scarce information visibility of the provider on the client’s processes. Originality/value To the author’s knowledge, this paper is among the first to address a still uncovered gap of the warehousing literature by illustrating a DST that exploits optimization and simulation techniques to quantify the impacts of the information availability on the warehousing operations performance. As a second novel contribution, this tool enables to create a digital twin of a WMS and foresee the evolution of the warehouse’s performance over time. Citation: Industrial Management & Data Systems PubDate: 2018-08-17T09:43:48Z DOI: 10.1108/IMDS-01-2018-0033
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to identify the key facilitators and inhibitors of fitness wearable technology (FWT) adoption and the intention to recommend this technology. Design/methodology/approach An innovative and integrated research model was developed by combining constructs from two well-established theoretical models, the extended unified theory of acceptance and use of technology (UTAUT2) and diffusion of innovation ( DOI ). The proposed research model was empirically validated using data collected from 392 respondents in China. The data was analyzed using the partial least squares method, a statistical analysis technique based on structural equation modeling. Findings The results indicate that performance expectancy, effort expectancy, social influence, habit, compatibility and innovativeness have significant direct and indirect effects on FWT adoption and the intention to recommend it. The significance of people’s intention to recommend FWT to others in social networking sites (e.g. Facebook, Weibo, and WeChat) is also confirmed. Practical implications The findings may facilitate the design and implementation of FWT products, applications and functionalities that can achieve high consumer acceptance and positive recommendations in social networks. Originality/value This study is among the first to investigate FWT adoption from behavioral, social and environmental perspectives. It also highlights the importance of social marketing campaigns and suggests directions of future wearable technology adoption research. Citation: Industrial Management & Data Systems PubDate: 2018-08-17T09:40:37Z
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to develop a decision support system to consider geographic information, logistics information and greenhouse gas (GHG) emission information to solve the proposed green inventory routing problem (GIRP) for a specific Taiwan publishing logistics firm. Design/methodology/approach A GIRP mathematical model is first constructed to help this specific publishing logistics firm to approximate to the optimal distribution system design. Next, two modified Heuristic-Tabu combination methods that combine savings approach, 2-opt and 1-1 λ-interchange heuristic approach with two modified Tabu search methods are developed to determine the optimum solution. Findings Several examples are given to illustrate the optimum total inventory routing cost, the optimum delivery routes, the economic order quantities, the optimum service levels, the reorder points, the optimum common review interval and the optimum maximum inventory levels of all convenience stores in these designed routes. Sensitivity analyses are conducted based on the parameters including truck loading capacity, inventory carrying cost percentages, unit shortage costs, unit ordering costs and unit transport costs to support optimal distribution system design regarding the total inventory routing cost and GHG emission level. Originality/value The most important finding is that GIRP model with reordering point inventory control policy should be applied for the first replenishment and delivery run and GIRP model with periodic review inventory control policy should be conducted for the remaining replenishment and delivery runs based on overall simulation results. The other very important finding concerning the global warming issue can help decision makers of GIRP distribution system to select the appropriate type of truck to deliver products to all retail stores located in the planned optimal delivery routes depending on GHG emission consumptions. Citation: Industrial Management & Data Systems PubDate: 2018-08-15T11:58:29Z DOI: 10.1108/IMDS-11-2017-0533
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose This paper posits, develops and tests the effects of general environmental awareness factors on consumers’ intentions in the Environmental Awareness Purchasing Intention Model. Environmental awareness is tested within the context of purchasing vehicles and, thus, vehicle relevant factors (perceived quality and self-image) are also included. Further, the purpose of this paper is to explain the relative contribution of general environmental awareness factors on purchasing intentions compared to quality and self-image. Design/methodology/approach The main thrust of the research involved a survey of 248 young automobile buyers from a large public university in Texas, USA. The data were analyzed using both multiple regression and partial least square-structural equation modeling (PLS-SEM). Findings Environmental attitude has a positive impact on purchasing intention, while perceived control toward environmentally responsible behavior has a negative impact. Results also show a positive impact of quality and self-image on intention to purchase environmentally friendly cars. Furthermore, the results reveal that environmental awareness factors explain less variance than perceived quality. At the same time, the results show that environmental factors, relatively, explain more variance in the decision-making process than self-image. Originality/value This is the first study to examine the relationship between general environmental awareness and the intention to purchase an environmentally friendly car. This study contributes to sustainable consumption literature in operations management. The paper also provides insights for developing managerial guidelines for car manufacturers based on the understanding of factors influencing environmentally friendly car purchasing intentions. Citation: Industrial Management & Data Systems PubDate: 2018-08-15T10:56:20Z DOI: 10.1108/IMDS-12-2017-0591
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to compare the relative impacts of trust and risk on individual’s transaction intention in consumer-to-consumer (C2C) e-marketplaces from both the buyers’ and the sellers’ perspectives. Design/methodology/approach Two surveys were used to collect data regarding buyers’ and sellers’ perceptions and transaction intentions at a typical C2C e-marketplace. Partial least squares was used to analyze the data. A complementary qualitative study was conducted to triangulate the results from the quantitative study. Findings Institution-based trust (IBT) exerts a stronger influence on transaction intentions for buyers than for sellers. Sellers perceive a stronger impact of trust in intermediary (TII) than buyers on transaction intentions. The impacts of perceived risk in transactions are not different between buyers and sellers. Furthermore, IBT mediates the impacts of TII and perceived risk on transaction intentions for buyers. Research limitations/implications The results indicate that the impacts of trust and risk on transaction intention in e-marketplaces do differ between buyers and sellers. This suggests a need to further investigate the buyer–seller difference in online transactions. Practical implications Intermediaries need to focus on different types of trust-building mechanisms when attracting buyers and sellers to make transactions in the e-marketplace. Originality/value C2C e-marketplaces cannot survive without participation from both buyers and sellers. Most prior research is conducted from the buyers’ perspective. This research sets a starting point for future research to further explore the differences between buyers’ and sellers’ behavior in C2C e-commerce environments. Citation: Industrial Management & Data Systems PubDate: 2018-08-15T10:50:19Z DOI: 10.1108/IMDS-10-2017-0489
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Although lean thinking is deemed to be a gold standard of modern production management, a lot of scepticism still remains regarding its applicability in small- and medium-sized enterprises (SMEs). The purpose of this paper is to understand the perception of lean in SMEs and establish the relationship between lean adoption and operational performance. Design/methodology/approach With the help of a survey, data were collected from 425 SMEs in India and analyzed using structural equation modeling. Findings Operational performance of the firms was found to be positively related to lean implementation. Originality/value This study also furnishes practitioners with a better understanding of lean thinking in SMEs and its impact on performance. Citation: Industrial Management & Data Systems PubDate: 2018-08-14T02:05:57Z DOI: 10.1108/IMDS-02-2018-0088
Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to provide implementation insights and implications regarding the strategic orientations of servitization by testing its impacts on firm performance, including financial performance and customer service performance. Design/methodology/approach Empirical research is conducted using an online survey disseminated to manufacturing firms in Southeast China. This research develops and verifies a strategic fit framework to understand the relationship between the strategic orientation of servitization and service innovation (SI), and its resulting impacts on firm performance. Findings The results show that service orientation (SO) has direct positive impacts on firm performance in the manufacturing sector. Customer orientation (CO) and learning orientation (LO) have no direct impact on firm performance, although they have indirect impacts on it via the mediating role of SI capability. Moreover, SO has a similar indirect impact on firm performance via SI capability. Research limitations/implications The survey focuses only on China; future studies should verify whether different cultural backgrounds impact the research results. Practical implications The results suggest that firms should build up three strategic orientations (SO, CO and LO) for implementing servitization to facilitate SI capability and, thus, to improve firm performance. Originality/value This research contributes to enhancing the theory of servitization by developing a strategic fit model of servitization and revealing the impact mechanism of servitization in the manufacturing sector. Citation: Industrial Management & Data Systems PubDate: 2018-08-14T02:03:36Z DOI: 10.1108/IMDS-10-2017-0485
First page: 1730 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to explore how a foreign invested manufacturing company’s (FIMC) components sourcing process evolves in order to improve its supply chain outcomes in the context of China’s processing trade. Design/methodology/approach Grounded in the theory bases of the international sourcing process and supply chain integration, this study utilizes a single-case-study approach with a small- to medium-sized FIMC engaged in China’s processing trade. Findings This study identifies three stages of the components sourcing process: simple assembly stage, components localization stage and supply chain integration stage. In addition, the case study suggests that the type of processing trade evolves from processing with supplied materials to processing with imported materials as the sourcing process proceeds through the three stages and the internal and external environments change. Originality/value To our knowledge, this paper is the first to focus on an FIMC’s components sourcing process in the context of China’s processing trade. It contributes to a better understanding of how FIMCs progress through the components sourcing process and apply different types of processing trade in China to maximize their supply chain outcomes. Citation: Industrial Management & Data Systems PubDate: 2018-08-10T02:58:41Z DOI: 10.1108/IMDS-11-2017-0528
First page: 1749 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to examine the role of supply chain integration (SCI) in improving sustainability management practices (SMPs) and performance. Design/methodology/approach Based on data collected from 931 manufacturing firms in multiple countries and regions, the authors conducted a structural equation modeling analysis to test the proposed hypotheses. Findings The findings suggest that supplier and customer integration are vital enablers for both intra- and inter-organizational SMPs. The results also reveal that both intra- and inter-organizational SMPs are significantly and positively associated with sustainability performance (i.e. economic, environmental and social performance) and function as complements to jointly enhance environmental and social performance. Originality/value This study incorporates SCI into the sustainability literature, providing a new perspective on sustainability and supply chain management research. Citation: Industrial Management & Data Systems PubDate: 2018-08-15T11:59:49Z DOI: 10.1108/IMDS-01-2018-0004
First page: 1766 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to empirically examine the factors that influence the acceptance and use of mobile casual games. Design/methodology/approach A theoretical model is proposed based on the theory of reasonable action, the uses and gratifications theory, the network externalities (NEs) paradigm and the human–computer interaction literature. An empirical study was conducted through an online survey of mobile casual gamers in Spain, using a convenience sample. The proposed model was tested by an analysis of the collected data through a structural equation model using the partial least squares method. Findings The results indicate that human–mobile game interaction and NEs have a significant indirect impact on intention to play (IP), through utilitarian, hedonic and relational motivations. In addition, the full mediation effect of attitude was found between these constructs and IP, which is a very important determinant of actual use. Originality/value This study is among the few that focuses on users’ acceptance of mobile games apps, the features of which differ significantly from personal computer and console games. It highlights the effects of human–game interaction and NEs on the adoption of mobile casual games. Hence, the study contributes to the theoretical and practical understanding of the factors that lead users to adopt an entertainment mobile application. Citation: Industrial Management & Data Systems PubDate: 2018-08-14T02:04:56Z DOI: 10.1108/IMDS-11-2017-0544
First page: 1787 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose The purpose of this paper is to examine the multiple paths of absorptive capacity’s (AC) effect on business performance (BP): direct effect and indirect effects through innovation and mass customization (MC). Design/methodology/approach The authors examined the role of innovation and MC capability on the relationship between AC and BP. Data from 278 Chinese firms in four manufacturing industries collected by questionnaire are used to empirically examine the proposed model by Structural equation modeling. Findings The results show that AC can directly enhance BP, and indirectly through innovation and MC capability. The study also finds that MC capability has a stronger mediating effect than innovation. Originality/value Prior studies have not yet built linkages between AC and BP with both innovation and MC’s effects. This study provides empirical evidence of the effects of AC on BP and three paths are discussed including AC’s direct effect and indirect effects through innovation and MC to firm’s BP. This study provides a new direction for executives to better understand the movement of knowledge along supply chain and in intra-organizational environment, and of the importance of innovation and MC capability since they are essential carriers for BP enhancement. Citation: Industrial Management & Data Systems PubDate: 2018-08-20T12:24:11Z DOI: 10.1108/IMDS-09-2017-0416
First page: 1804 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been conducted on the multi-class sentiment analysis of tweets. The purpose of this paper is to consider the popularity of emojis on Twitter and investigate the feasibility of an emoji training heuristic for multi-class sentiment classification of tweets. Tweets from the “2016 Orlando nightclub shooting” were used as a source of study. Besides, this study also aims to demonstrate how mapping can contribute to interpreting sentiments. Design/methodology/approach The authors presented a methodological framework to collect, pre-process, analyse and map public Twitter postings related to the shooting. The authors designed and implemented an emoji training heuristic, which automatically prepares the training data set, a feature needed in Big Data research. The authors improved upon the previous framework by advancing the pre-processing techniques, enhancing feature engineering and optimising the classification models. The authors constructed the sentiment model with a logistic regression classifier and selected features. Finally, the authors presented how to visualise citizen sentiments on maps dynamically using Mapbox. Findings The sentiment model constructed with the automatically annotated training sets using an emoji approach and selected features performs well in classifying tweets into five different sentiment classes, with a macro-averaged F-measure of 0.635, a macro-averaged accuracy of 0.689 and the MAEM of 0.530. Compared to those experimental results in related works, the results are satisfactory, indicating the model is effective and the proposed emoji training heuristic is useful and feasible in multi-class TSA. The maps authors created, provide a much easier-to-understand visual representation of the data, and make it more efficient to monitor citizen sentiments and distributions. Originality/value This work appears to be the first to conduct multi-class sentiment classification on Twitter with automatic annotation of training sets using emojis. Little attention has been paid to applying TSA to monitor the public’s attitudes towards terror attacks and country’s gun policies, the authors consider this work to be a pioneering work. Besides, the authors have introduced a new data set of 2016 Orlando Shooting tweets, which will be made available for other researchers to mine the public’s political opinions about gun policies. Citation: Industrial Management & Data Systems PubDate: 2018-09-05T10:45:51Z DOI: 10.1108/IMDS-12-2017-0582
First page: 1821 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose Despite existing advances in information technology infrastructure services (ITISs), there remains no consensus in the literature regarding what dimensions or criteria are best suited for the measurement of their quality. The purpose of this paper is to fill this gap, proposing a methodological approach to measuring the quality of ITISs, as perceived by users. Design/methodology/approach Cronbach’s α and item-total correlations were used to measure the reliability of the questionnaire; multiple linear regression analysis was employed to determine the items (criteria) most related to the quality of ITISs; and finally, importance–performance analysis was conducted to determine the most critical criteria in service provision. An exploratory study was conducted to evaluate the quality of ITISs at a Brazilian university. Findings Control of the activities of the information technology (IT) team, periodic maintenance of hardware and software, the security policy and the skill of the labor affect the quality of services most, relative to the dimensions of infrastructure, people and processes. Practical implications The results indicate what dimensions and items should be considered by IT managers to improve the quality of ITISs. Special attention should be paid to the effective use of equipment, software and network infrastructure: it should be ensured that these are in good working order and can be utilized by users who expect to be trained to take advantage of their functions. Originality/value This paper shows how to integrate relevant techniques to assess the quality of ITISs. An original set of criteria to evaluate the quality of ITISs, derived from a systematic review of the literature, is suggested. Citation: Industrial Management & Data Systems PubDate: 2018-08-10T03:00:21Z DOI: 10.1108/IMDS-09-2017-0415
First page: 1837 Abstract: Industrial Management & Data Systems, Ahead of Print. Purpose This purpose of this paper is to evaluate Millennials’ intention to use service mobile apps and assess gender as a moderator. Design/methodology/approach An extended technology acceptance model framework that includes information quality and self-efficacy guides this research. PLS-SEM is used to evaluate the data and test the hypotheses. Findings The study reveals that information quality, self-efficacy, perceived ease of use and usefulness, and attitude influence Millennials’ intentions to use service mobile apps. Additionally, gender is found to partially moderate the results. Practical implications Service companies that rely on mobile apps to deliver services ought to consider the disparities among the Millennial generation, increasing the likelihood that Millennial customers will adopt service mobile apps and that they receive acceptable customer experiences. Originality/value This paper examines the factors influencing adoption and use of service mobile apps among Millennials and examines gender as a moderator. Additionally, guidelines for service mobile app design are included. Citation: Industrial Management & Data Systems PubDate: 2018-08-15T10:53:39Z DOI: 10.1108/IMDS-10-2017-0479
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