Pages: 2142 - 2170 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2142-2170, December 2017. Purpose The purpose of this paper is twofold. First, to propose an operational model for aircraft maintenance routing problem (AMRP) rather than tactical models that are commonly used in the literature. Second, to develop a fast and responsive solution method in order to cope with the frequent changes experienced in the airline industry. Design/methodology/approach Two important operational considerations were considered, simultaneously. First one is the maximum flying hours, and second one is the man-power availability. On the other hand, ant colony optimization (ACO), simulated annealing (SA), and genetic algorithm (GA) approaches were proposed to solve the model, and the upper bound was calculated to be the criteria to assess the performance of each meta-heuristic. After attempting to solve the model by these meta-heuristics, the authors noticed further improvement chances in terms of solution quality and computational time. Therefore, a new solution algorithm was proposed, and its performance was validated based on 12 real data from the EgyptAir carrier. Also, the model and experiments were extended to test the effect of the operational considerations on the profit. Findings The computational results showed that the proposed solution algorithm outperforms other meta-heuristics in finding a better solution in much less time, whereas the operational considerations improve the profitability of the existing model. Research limitations/implications The authors focused on some operational considerations rather than tactical considerations that are commonly used in the literature. One advantage of this is that it improves the profitability of the existing models. On the other hand, identifying future research opportunities should help academic researchers to develop new models and improve the performance of the existing models. Practical implications The experiment results showed that the proposed model and solution methods are scalable and can thus be adopted by the airline industry at large. Originality/value In the literature, AMRP models were cast with approximated assumption regarding the maintenance issue, while neglecting the man-power availability consideration. However, in this paper, the authors attempted to relax that maintenance assumption, and consider the man-power availability constraints. Since the result showed that these considerations improve the profitability by 5.63 percent in the largest case. The proposed operational considerations are hence significant. Also, the authors utilized ACO, SA, and GA to solve the model for the first time, and developed a new solution algorithm. The value and significance of the new algorithm appeared as follow. First, the solution quality was improved since the average improvement ratio over ACO, SA, and GA goes up to 8.30, 4.45, and 4.00 percent, respectively. Second, the computational time was significantly improved since it does not go beyond 3 seconds in all the 12 real cases, which is considered much lesser compared to ACO, SA, and GA. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:43:48Z DOI: 10.1108/IMDS-11-2016-0475
Pages: 2171 - 2193 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2171-2193, December 2017. Purpose Carbon footprint assessment requires a holistic approach, where all possible lifecycle stages of products from raw material extraction to the end of life are considered. The purpose of this paper is to develop an analytical sustainability assessment framework to assess the carbon footprint of US economic supply chains from two perspectives: supply chain layers (tiers) and carbon footprint sources. Design/methodology/approach The methodology consists of two phases. In the first phase, the data were collected from EORA input output and environmental impact assessment database. In the second phase, 48 input-output-based lifecycle assessment models were developed (seven CO2 sources and total CO2 impact, and six supply chain tiers). In the third phase, the results are analyzed by using data visualization, data analytics, and statistical approaches in order to identify the heavy carbon emitter industries and their percentage shares in the supply chains by each layer and the CO2 source. Findings Vast majority of carbon footprint was found to be attributed to the power generation, petroleum refineries, used and secondhand goods, natural gas distribution, scrap, and truck transportation. These industries dominated the entire supply chain structure and found to be the top drivers in all six layers. Practical implications This study decomposes the sources of the total carbon footprint of US economic supply chains into six layers and assesses the percentage contribution of each sector in each layer. Thus, it paves the way for quantifying the carbon footprint of each layer in today’s complex supply chain structure and highlights the importance of handling CO2 source in each layer separately while maintaining a holistic focus on the overall carbon footprint impacts in the big picture. In practice, one size fits all type of policy making may not be as effective as it could be expected. Originality/value This paper provides a two-dimensional viewpoint for tracing/analyzing carbon footprint across a national economy. In the first dimension, the national economic system is divided into six layers. In the second dimension, carbon footprint analysis is performed considering specific CO2 sources, including energy production, solvent, cement and minerals, agricultural burning, natural decay, and waste. Thus, this paper contributes to the state-of-art sustainability assessment by providing a comprehensive overview of CO2 sources in the US economic supply chains. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:45:10Z DOI: 10.1108/IMDS-11-2016-0473
Pages: 2194 - 2209 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2194-2209, December 2017. Purpose The purpose of this paper is to empirically investigate the effects of competence and goodwill trust on knowledge creation and the moderating effects of legal inadequacy on those relationships. Design/methodology/approach A questionnaire survey was used to collect data from 196 research and development alliances in China. Hierarchical moderated regression was used to test the research hypotheses. Findings The authors find that competence trust has a positive and linear relationship with knowledge creation while goodwill trust has an inverted U-shaped relationship with it. The results also reveal that the inverted U-shaped relationship between goodwill trust and knowledge creation is stronger when legal inadequacy is high, while the impact of competence trust on knowledge creation is not influenced by legal inadequacy. Originality/value The findings provide insights into the distinctive effects of competence and goodwill trust on knowledge creation in partnerships, deepening current understandings of the bright and dark sides of inter-firm trust. This study also clarifies the influences of legal inadequacy on the effectiveness of competence and goodwill trust, which enhances existing knowledge about the impact of legal systems on the relationships between inter-firm trust and knowledge management. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:43:53Z DOI: 10.1108/IMDS-11-2016-0482
Pages: 2210 - 2226 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2210-2226, December 2017. Purpose Consumers can face a situation of information asymmetry in electronic shopping (ES). The purpose of this paper to examine the relationships between: relational variables such as satisfaction, trust and perceived opportunism; and website cues (cognitive signals such as security and personalization, and experiential signals, such as design and entertainment). Design/methodology/approach The paper opted for the structural equation methodology to analyze data collected from 447 Spanish e-shoppers. Findings Results show different factors that relate to satisfaction, trust and perceived opportunism in ES. Satisfactory experience with ES and entertainment emerge as the most relevant factors to achieve trust and prevent perceived opportunism in e-commerce. Originality/value The five contributions of this study are: the introduction of variables from several theoretical approaches to the study of an agency problem in e-commerce; the study of different ways to gain buyer trust and reduce perceived opportunism in an electronic shopper-vendor relationship; the application of signaling theory as part of the process of helping the principal (e-shopper) to solve their shopping problem in a context of information asymmetry; the analysis of the impact of external cues from e-vendor/site, which allows for a comparison between internal experiences and external quality signals; and the study of entertainment as an important hedonic variable in order to have satisfied and confident e-shoppers. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:49Z DOI: 10.1108/IMDS-08-2016-0315
Pages: 2227 - 2240 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2227-2240, December 2017. Purpose The purpose of this paper is to investigate social shopping deals and their impacts on review metrics at an online review site, Yelp and to compare the review metrics of the restaurant businesses and the health and wellness businesses to understand how social shopping deals affects them. Design/methodology/approach This study adopts a multiple regression model to analyse the effect of seven independent variables on the dependent variable, the growth rate of reviews which is a proxy of sales growth. This sample consisted of the review data of 134 merchants which offered social shopping deals at Groupon in 2011. The online review data of these merchants were collected in 2015 to analyse the relationship between the deals and the grow rate of the reviews. Findings For the restaurant businesses, there is a positive persuasive effect of Groupon customers’ review score on the growth rate of the reviews and consequently on the sale growth. For the health and wellness businesses, there are a positive persuasive effect of the regular customers’ review score on the growth rate of the reviews and a negative awareness effect of the number of Groupon reviews on the growth rate of the reviews. The review data also show that the Groupon customers of the health and wellness businesses are three times more likely to post their reviews than those of the restaurant businesses. Research limitations/implications First, while the author limited the study to the seven independent variables, additional variables may exist. These additional variables may also influence the number of reviews, too. Future research needs to identify such variables to build a comprehensive model. Second, future research needs to address other types of businesses, such as education and entertainment, and compare differences between them. Third, while the study focussed on the review score and the number of reviews, a more in-depth analysis of the comments using sentiment analysis and social network analysis may shed additional insights on their review activities. Originality/value Despite the potential significance of customers’ reviews about social shopping deals, the critical mass of empirical studies still lacks in this area. The study contributes to the literature of this field by investigating the effect of social shopping deals on the customers’ online reviews. This study provides practical guidance for the improvement of online reviews about social shopping deals. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:41Z DOI: 10.1108/IMDS-09-2016-0378
Pages: 2241 - 2262 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2241-2262, December 2017. Purpose Enterprise systems (ESs) are hard to maintain, since they embed a large fraction of organisational data and tasks, which are often intertwined and highly interdependent. The purpose of this paper is to propose a methodology for enterprise resource planning (ERP) post-implementation change management to support business analysts during perfective maintenance. Design/methodology/approach The methodology draws a parallel line with engineering change management and considers the steps of mapping the dependencies among ES components, understanding the ripple effects of change, and defining metrics to quantify and assess the impact of change. The methodology is instantiated in the case of ERP systems, for which a tool has also been implemented and evaluated by ERP implementation experts. Findings Experts positively evaluated the proposed methodology. General design principles to instantiate the methodology in the case of systems other than ERP have been derived. Originality/value While existing ESs change management methodologies help to identify the need for change, the proposed methodology help to structure the change process, supporting the task of perfective maintenance in an efficient way. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:03Z DOI: 10.1108/IMDS-11-2016-0506
Pages: 2263 - 2286 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2263-2286, December 2017. Purpose The purpose of this paper is to present the state-of-the-art E-commerce logistics in supply chain management by investigating worldwide implementations and corresponding models together with supporting techniques via furniture industry. Design/methodology/approach Typical E-commerce logistics companies from North America, Europe, and Asia Pacific are comprehensively investigated so as to get the lessons and insights from these practices. Findings Future technologies like Internet of Things, Big Data Analytics, and Cloud Computing would be possibly adopted to enhance the E-commerce logistics in terms of system level, operational level, and decision-making level that may be real time and intelligent in the next decade. Research limitations/implications This paper takes the furniture industry for example to illustrate the E-commerce logistics and supply chain management (LSCM). Other industries like electronic appliance industry are not considered. Practical implications Opportunities and future perspectives are summarized from practical implementations so that interested parties like E-commerce and logistics companies are able to get some guidance when they are contemplating the business. Social implications E-commerce is booming with the development of new business models and will be continuously boosted in the near future. With large number of enterprises carrying out E-commerce, logistics has been largely influenced. Originality/value Insights and lessons from this paper are significant for academia and practitioners for considering E-commerce LSCM. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:16Z DOI: 10.1108/IMDS-09-2016-0398
Pages: 2287 - 2304 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2287-2304, December 2017. Purpose Many cities implement freight traffic restriction policy (FTRP) intending to reduce traffic congestion and air pollution. At the same time, city distribution had some negative effects. The purpose of this paper is therefore to study the freight group behavior under FTRP, and to provide some recommendations for the government. Design/methodology/approach This paper establishes a city distribution system model built by a simulation method of Agent, which includes the complex adaptability of freight individual, event of restriction policy, the influence factor of freight group behavior and its changes from the perspective of restriction policy. The rules of microscopic freight group behavior to macroscopic freight group behavior, the effects on freight group behavior exerted by restriction policy and the dynamic mechanism of freight group behavior are all studied. The model is also simulated with the traffic data of Beijing in China. Findings Theoretical results ensure that restriction of the passport is not the sole reason that may produce illegal trucks, and other measures need to be taken to solve the traffic problems. And in the long run, increasing fines has a greater effect than strengthening supervision frequency on illegal trucks reduction. Originality/value From city distribution perspective, this paper studied freight group behavior under FTRP. This paper also applied the Agent modeling method to build a model of urban distribution system in the FTRP. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:43:43Z DOI: 10.1108/IMDS-10-2016-0448
Pages: 2305 - 2324 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2305-2324, December 2017. Purpose Industry 4.0 envisions a future of networked production where interconnected machines and business processes running in the cloud will communicate with one another to optimize production and enable more efficient and sustainable individualized/mass manufacturing. However, the openness and process transparency of networked production in hyperconnected manufacturing enterprises pose severe cyber-security threats and information security challenges that need to be dealt with. The paper aims to discuss these issues. Design/methodology/approach This paper presents a distributed trust model and middleware for collaborative and decentralized access control to guarantee data transparency, integrity, authenticity and authorization of dataflow-oriented Industry 4.0 processes. Findings The results of a performance study indicate that private blockchains are capable of securing IoT-enabled dataflow-oriented networked production processes across the trust boundaries of the Industry 4.0 manufacturing enterprise. Originality/value This paper contributes a decentralized identity and relationship management for users, sensors, actuators, gateways and cloud services to support processes that cross the trust boundaries of the manufacturing enterprise, while offering protection against malicious adversaries gaining unauthorized access to systems, services and information. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:43:58Z DOI: 10.1108/IMDS-10-2016-0419
Pages: 2325 - 2339 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2325-2339, December 2017. Purpose The purpose of this paper is to build a compact and accurate classifier for high-dimensional classification. Design/methodology/approach A classification approach based on class-dependent feature subspace (CFS) is proposed. CFS is a class-dependent integration of a support vector machine (SVM) classifier and associated discriminative features. For each class, our genetic algorithm (GA)-based approach evolves the best subset of discriminative features and SVM classifier simultaneously. To guarantee convergence and efficiency, the authors customize the GA in terms of encoding strategy, fitness evaluation, and genetic operators. Findings Experimental studies demonstrated that the proposed CFS-based approach is superior to other state-of-the-art classification algorithms on UCI data sets in terms of both concise interpretation and predictive power for high-dimensional data. Research limitations/implications UCI data sets rather than real industrial data are used to evaluate the proposed approach. In addition, only single-label classification is addressed in the study. Practical implications The proposed method not only constructs an accurate classification model but also obtains a compact combination of discriminative features. It is helpful for business makers to get a concise understanding of the high-dimensional data. Originality/value The authors propose a compact and effective classification approach for high-dimensional data. Instead of the same feature subset for all the classes, the proposed CFS-based approach obtains the optimal subset of discriminative feature and SVM classifier for each class. The proposed approach enhances both interpretability and predictive power for high-dimensional data. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:45:42Z DOI: 10.1108/IMDS-11-2016-0491
Pages: 2340 - 2363 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2340-2363, December 2017. Purpose Based on the theory of social networks, it is crucial to enhance information superiority through joint venture capital (VC). The purpose of this paper is to explore the impacts of different roles’ structural and relational embeddedness on the information superiority of joint VC alliances. Design/methodology/approach The authors design the multiple linear regression models to investigate the leader’s investment ratio from a network embeddedness perspective. Panel data analysis and robustness tests are adopted based on the data from Chinese VCs Database. Findings The results show that VC leaders enjoy information search advantages because of their better network positions, while their followers lack this superiority. Information sharing among investors and investees may enhance the influences of structural embeddedness on investors’ information search advantages. Joint VC’s scale and its number of leaders could also increase VC alliances’ information superiority. Originality/value This research provides a more holistic understanding of the formation of joint VC alliances’ information superiority from a social network perspective. Both VC managers and social planners can seek guidance from this study to implement better strategies and policies to promote information symmetry in the VC market. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:39Z DOI: 10.1108/IMDS-09-2016-0359
Pages: 2364 - 2380 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2364-2380, December 2017. Purpose With the increasingly collaborative nature of innovation and the expanding role of digital platforms on inter-firm collaboration, the purpose of this paper is to investigate the impacts of digital platforms on collaborative innovation capability (CIC) under conditions of two distinctive governance mechanisms. Furthermore, the competitive benefits of CIC at different levels of environmental uncertainty are examined to clarify the performance of collaborative innovation. Design/methodology/approach The research model is proposed based on dynamic capabilities theory, information technology (IT)-enabled organizational capability and governance mechanisms literature, and then validated by using partial least squares with data collected from 200 Chinese firms that engage in digital collaboration with their major channel distributors. Findings Empirical results show that the enabling effect of digital platforms capability on CIC is positively moderated by relational governance while negatively moderated by formal governance, and both governance mechanisms directly and positively influence CIC; the positive relationship between CIC and competitive performance is stronger for higher level of environmental uncertainty; and CIC is the key mediator converting digital platforms capability into competitive performance. Originality/value This study enriches the existing literatures in IT-innovation relationship by not only surfacing the interplay of digital platforms capability with two distinctive governance mechanisms in building CIC, but also clarifying the competitive benefits of CIC in an uncertain environment. Moreover, this study helps explain the controversial issue of the business value of IT capability by discovering the mediating role of CIC. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:06Z DOI: 10.1108/IMDS-09-2016-0392
Pages: 2381 - 2399 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2381-2399, December 2017. Purpose The keywords from patent documents contain a lot of information of technology. If we analyze the time series of keywords, we will be able to understand even more about technological evolution. The previous researches of time series processes in patent analysis were based on time series regression or the Box-Jenkins methodology. The methods dealt with continuous time series data. But the keyword time series data in patent analysis are not continuous, they are frequency integer values. So we need a new methodology for integer-valued time series model. The purpose of this paper is to propose modeling of integer-valued time series for patent analysis. Design/methodology/approach For modeling frequency data of keywords, the authors used integer-valued generalized autoregressive conditional heteroskedasticity model with Poisson and negative binomial distributions. Using the proposed models, the authors forecast the future trends of target keywords of Apple in order to know the future technology of Apple. Findings The authors carry out a case study to illustrate how the methodology can be applied to real problem. In this paper, the authors collect the patent documents issued by Apple, and analyze them to find the technological trend of Apple company. From the results of Apple case study, the authors can find which technological keywords are more important or critical in the entire structure of Apple’s technologies. Practical implications This paper contributes to the research and development planning for producing new products. The authors can develop and launch the innovative products to improve the technological competition of a company through complete understanding of the technological keyword trends. Originality/value The retrieved patent documents from the patent databases are not suitable for statistical analysis. So, the authors have to transform the documents into structured data suitable for statistics. In general, the structured data are a matrix consisting of patent (row) and keyword (column), and its element is an occurred frequency of a keyword in each patent. The data type is not continuous but discrete. However, in most researches, they were analyzed by statistical methods for continuous data. In this paper, the authors build a statistical model based on discrete data. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:45:37Z DOI: 10.1108/IMDS-01-2017-0023
Pages: 2400 - 2416 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2400-2416, December 2017. Purpose The ability to make use of social network sites (SNSs) to promote new products and facilitate positive word of mouth around new product launch (NPL) presents an important opportunity. However, the mechanisms and motivations of SNS users are not well understood and businesses frequently fail to realise these opportunities. The purpose of this paper is to examine some of the forces that motivate people to spend time on SNS sites and how these motivations are related with people’s propensity to engage in behaviours that can be beneficial for NPL. Design/methodology/approach Hypotheses are tested using data collected using an online survey from a broad sample of SNS users worldwide. Findings People who spend time on SNSs to be challenged, to escape, or to connect with others are more likely than other users to pay attention to advertisements on SNS. Users that spend time on SNSs in the pursuit of information, to be challenged, or to connect with others are more likely than other users to provide word of mouth reviews and recommendations about products. Research limitations/implications The authors make an empirical contribution to knowledge by providing evidence about the categories of user motivations for engagement with SNSs that might be related with their contributions to NPL activities, namely, paying attention to advertisements and providing WOM recommendations. Practical implications By understanding what motivates SNS users, firms can identify potentially valuable users and develop a more strategic and targeted approach to NPL. This can help firms turn disappointing social media campaigns into more successful ones. Social implications Whilst the growth in usage of SNS has important implications for business and NPL there are also wider societal implications. Arguably, even before the widespread adoption of SNSs, society has been in a state of flux and transition as people sought to liberate themselves from the norms and social codes of previous generations. We have witnessed a rise of individualism, associated with values such as personal freedom and where people actively construct their own identities. Somewhat ironically, individualism has motivated people to seek alternative social activities and form communities, such as those on SNSs where they can fulfil their need for connection and belonging. SNSs appear to have accelerated this trend. Originality/value This study provides new insights about the use of SNSs for NPL and what motivates users to engage in behaviours that are beneficial to NPL. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:45:15Z DOI: 10.1108/IMDS-11-2016-0472
Pages: 2417 - 2430 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2417-2430, December 2017. Purpose Patent contains vast information on developed technologies because of the patent system. So, it is important to analyze patent data for understanding technologies. Most previous studies on patent analysis were focused on the technology itself. Their research results lacked the consideration of products. But the patent analysis based on products is crucial for company because a company grows by sales of competitive products. The purpose of this paper is to propose a novel methodology of patent analysis for product-based technology. This study contributes to the product development strategy of a company. Design/methodology/approach The primary goal for developing technology is to release a new product. So it is important to analyze the technology based on the product. In this study, the authors analyze Apple’s technologies based in iPod, iPhone, and iPad. In addition, the authors propose a new methodology to analyze product-based technology. The authors call this an integrated social network mining (ISNM). In the ISNM, the authors carry out a social network analysis (SNA) according to each product of Apple, and integrate all SNA results of iPod, iPhone, and iPad using the technological keywords. Findings In this case study, the authors analyze Apple’s technologies according to Apple’s innovative products, such as the iPod, iPhone, and iPad. From the ISNM results of Apple’s technology, the authors can find which technological detail is more important in overall structure of Apple’s technologies. Practical implications This study contributes to the management of technology including new product development, technological innovation, and research and development planning. To know the technological relationship between whole technologies based on products can be the source of intensification of technological competitiveness. Originality/value Most of studies on technology analysis were focused on patent technology itself. Though one of their research goals was to develop new product, they had their limits considering the products because they did not use the technology information in the technology analysis. The originality of this research is to use the product information in technology analysis using the proposed ISNM. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:45:45Z DOI: 10.1108/IMDS-10-2016-0441
Pages: 2431 - 2451 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2431-2451, December 2017. Purpose The purpose of this paper is to investigate the use contexts of personal computing devices in multiple steps and conducts an in-depth analysis for the use context of smartphones. The determinants of use context changes of smartphones are investigated using the technology-to-performance chain model. Design/methodology/approach In steps 1 and 2, a diary study method and 2014-2015 Korea media panel research data provided by the Korea Information Society Development Institute are used. Correspondence analysis, χ2 independence tests, and standardized residual analyses were conducted. In step 3, this study develops and validates a framework for use context changes using a survey method and structural equation modeling. Findings The results show that the use context of personal computing devices is represented differently and is clearly defined depending on the device used. Furthermore, the use context of smartphones has changed significantly because of the rapid growth of smartphone users and diverse usage patterns of smartphones. The research model results show that users expand the scope and frequency of smartphone use when they experience improved performance in everyday tasks and feel that smartphone content and functions could support everyday tasks better. Originality/value This study presents novel early stage research and presents empirical evidence and propositions in both exploratory and confirmatory ways. The main contribution of this study is to provide guidelines and general implications for other empirical studies on the use contexts of devices or information technology services. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:45:33Z DOI: 10.1108/IMDS-11-2016-0471
Pages: 2452 - 2467 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2452-2467, December 2017. Purpose The purpose of this paper is to investigate the consumer experience of flow in an online consumer shopping environment and use online consumer participants to examine how consumer pursuit of shopping value links in turn affects their satisfaction and unplanned purchase behavior. Design/methodology/approach The research model was tested using the data collected from 363 valid questionnaires. Structural equation modeling was employed to verify and validate the research model. Findings The results of this study show that perceived control of flow and concentration will positively affect consumer utilitarian value, while concentration and cognitive enjoyment will positively affect hedonic value. Further, the effect of utilitarian value on satisfaction is greater than that of hedonic value. Finally, hedonic value positively affects unplanned buying behavior. This research results may serve as a reference for online store operators. Research limitations/implications This study used cross-sectional data for its cause and effect analysis. Long-term conclusions based on this study are not possible. Future scholars may consider using a longitudinal approach. Practical implications The results of this study clearly demonstrate that e-commerce operators must construct environments that create flow experiences for shoppers by increasing their perceived control, concentration, and cognitive enjoyment. Doing so will create both utilitarian and hedonic values, making consumers feel satisfied with their shopping experience and leading them to make purchases not originally planned in their shopping list. Originality/value This study’s major contribution is its successful linkage of the dimensions of flow experience to purchase values. Moreover, it confirms that when online shoppers have an unselfconscious flow experience, they will experience both utilitarian and hedonic values, thus increasing their satisfaction. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:44:34Z DOI: 10.1108/IMDS-11-2016-0500
Pages: 2468 - 2484 Abstract: Industrial Management & Data Systems, Volume 117, Issue 10, Page 2468-2484, December 2017. Purpose In the era of climate change, industrial organizations are under increasing pressure from consumers and regulators to reduce greenhouse gas emissions. The purpose of this paper is to examine the effectiveness of product mix as a strategy to deliver the low carbon supply chain under the cap-and-trade policy. Design/methodology/approach The authors incorporate the cap-and-trade policy into the green product mix decision models by using game-theoretic approach and compare these decisions in a decentralized model and a centralized model, respectively. The research explores potential behavioral changes under the cap-and-trade in the context of a two-echelon supply chain. Findings The analysis results show that the channel structure has significant impact on both economic and environmental performances. An integrated supply chain generates more profits. In contrast, a decentralized supply chain has lower carbon emissions. The cap-and-trade policy makes a different impact on the economic and environmental performances of the supply chain. Balancing the trade-offs is critical to ensure the long-term sustainability. Originality/value The research offers many interesting observations with respect to the effect of product mix strategy on operational decisions and the trade-offs between costs and carbon emissions under the cap-and-trade policy. The insights derived from the analysis not only help firms to make important operational and strategic decisions to reduce carbon emissions while maintaining their economic competitiveness, but also make meaningful contribution to governments’ policy making for carbon emissions control. Citation: Industrial Management & Data Systems PubDate: 2017-11-21T03:43:35Z DOI: 10.1108/IMDS-02-2017-0054
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