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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.

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.

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.

The survey focuses only on China; future studies should verify whether different cultural backgrounds impact the research results.

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.

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.

Competitor analysis is a key component in operations management. Most business decisions are rooted in the analysis of rival products inferred from market structure. Relative to more traditional competitor analysis methods, the purpose of this paper is to provide operations managers with an innovative tool to monitor a firm’s market position and competitors in real time at higher resolution and lower cost than more traditional competitor analysis methods.

The authors combine the techniques of Web Crawler, Natural Language Processing and Machine Learning algorithms with data visualization to develop a big data competitor-analysis system that informs operations managers about competitors and meaningful relationships among them. The authors illustrate the approach using the fitness mobile app business.

The study shows that the system supports operational decision making both descriptively and prescriptively. In particular, the innovative probabilistic topic modeling algorithm combined with conventional multidimensional scaling, product feature comparison and market structure analyses reveal an app’s position in relation to its peers. The authors also develop a user segment overlapping index based on user’s social media data. The authors combine this new index with the product functionality similarity index to map indirect and direct competitors with and without user lock-in.

The approach improves on previous approaches by fully automating information extraction from multiple online sources. The authors believe this is the first system of its kind. With limited human intervention, the methodology can easily be adapted to different settings, giving quicker, more reliable real-time results. The approach is also cost effective for market analysis projects covering different data sources.

The purpose of this paper is to explore the ways in which firms nurture the business ecosystem for the development of emerging industries.

The research uses a qualitative research methodology with multiple case studies, namely two groups of companies in the PC and mobile business ecosystems.

This paper argues that industry renewal or emergence relies on the convergence and evolutionary process of the relevant business ecosystems. It analyzes the challenges faced by emerging industries, especially uncertainty issues concerning technology, application, and market. To deal with these uncertainty issues, firms within business ecosystems have developed two kinds of strategies: the core‐firm platform strategy and the niche‐firm supplementary strategy with an integrated supply chain. By using such strategies, firms together follow a three‐step process, including adjustment, adoption, and convergence, to help nurture the emerging industry.

This study only conducts interviews with industrial practitioners in the mobile computing business ecosystem, without covering other stakeholders.

First, the study describes the platform and supplementary strategies to deal with industry uncertainties; second, the analysis also identifies a three‐step collective behavior to achieve industry convergence.

The paper extends the study of business ecosystem theory into supply chain management by embedding different roles and strategies as well as collective behavior into a dynamic business environment.

The purpose of this paper is to explore a way to reshape the business ecosystem for existing industries by comparing traditional and Shanzhai networks in China. The research is also conducted on the supporting activities by service intermediaries in the ecosystem.

This research starts with a literature review on firms' strategy of industry maturity from three perspectives, including technology orientation, innovation orientation, and network orientation. The approach of multiple case studies is adopted to unveil the reshaping process of the business ecosystem. Two types of networks are mapped: the traditional mobile companies' network and the Shanzhai network. Intra‐network and inter‐network cross‐case analyses aim to generate the research findings and provide implications for different ecosystem players.

First, the relationship between industry and the business ecosystem is placed into a two by two matrix. Second, in order to reshape the business ecosystem, the traditional network prefers geographical dispersion to other countries to establish a new ecosystem, whereas the Shanzhai network brings niche substitutes to cut down industry entry barriers. Third, government agencies, as one of the service intermediaries, not only support the traditional network dispersion by providing preferential policies, but also support the reshaping process enabled by the Shanzhai network with legal guidance and resource capture. Fourth, other service intermediaries such as law firms, technology services, talent searchers, financial and industry associations, have greater impact on the Shanzhai network than on the traditional network. Fifth, from the comparison between these two networks, strategies to reshape the ecosystem can be differentiated in five aspects: frugal solution, platform enablement, organization recentralization, downstream innovation, and regulation adaptation.

This research further develops the observations into service intermediaries not only in core business but also in the extended level of the business ecosystem. The Shanzhai phenomenon also provides an excellent example implicating classical theories like cluster, innovation and global manufacturing virtual network. From a methodology perspective, this research combined the roadmap methods and cross‐case analysis. However, this study focuses more on Shanzhai network study than the traditional network.

Five nurturing strategies implicate small firms in the Shanzhai network and large firms in the traditional network as well as service intermediaries.

This paper is the first one to deeply study the relationship between industry and the business ecosystem in China, and the reshaping process of a mature business ecosystem from the traditional network, Shanzhai network and service intermediaries' perspectives.

The purpose of this paper is to explore the quality factors influencing customer satisfaction in the electronic commerce (e-commerce) context using a triadic view of customer-e-retailer-third-party logistics provider, and to investigate the impacts of service quality on customer satisfaction and loyalty in the e-retailing supply chain.

A literature review is used to determine the conceptual model and develop the measurement scales. Data are collected through a web survey mainly conducted in China. Structural equation modeling is used to analyze the collected data and test the research hypotheses.

The results verify the proposed service quality framework, consisting of two dimensions (electronic service (e-service) quality and logistics service quality), in the e-commerce context. The results indicate that e-service quality and logistics service quality are strongly linked to customer satisfaction; that is, with e-service and logistics service, respectively. e-Service quality positively impacts customer satisfaction with logistics services, but logistics service quality negatively impacts customer satisfaction with e-services. Moreover, customer satisfaction with e-services is positively associated with customer loyalty for both e-services and logistics services. However, customer satisfaction with logistics services has no direct impact on related customer loyalty, and negatively impacts customer loyalty with e-services.

The survey focusses only on China; future data should verify whether different cultural backgrounds will impact the research results.

The results show that e-retailers should not only focus on e-service quality, but also logistics service quality, which is critical to the success of e-commerce.

A two-dimensional (e-service and logistics) service quality framework is proposed and empirically assessed in the context of the e-retailing supply chain. These impacts of the path of service quality on customer satisfaction and loyalty are highlighted.

The purpose of this paper is to examine how business ecosystems evolve, what is the identity of business ecosystem and is the ecosystem identity static or dynamics. To understand the above questions, this paper is conducted on stone carving clusters in India.

The author engaged the ethnographic approach in this study. To sample stone carving clusters of India, the author followed the snowball sampling method. Further, the author did collect the information by informal personal discussions, focus group discussions and participant observations. Furthermore, the thematic analysis and interpretative phenomenological analysis were applied to process the data. The validity and reliability of the method was ascertained by testing the credibility, dependability, confirmability and transferability.

The author found that the business ecosystem of stone carving was dynamic, and it was transformed from the buyer-driven ecosystem to the supplier-driven ecosystem. The identities of the early stage business ecosystem and the late stage ecosystem were analyzed through product, network and information flow. The author developed a structural framework to conceptualize the identity domain of the business ecosystem and the author named it as “nature-conduct-performance model.” Also, the author conceptualized the identity evolution, the influence of social system on business ecosystem identity, and identity-based conflicts and identity-based cooperation in the stone carving business ecosystem.

This study is making additional theoretical contribution in conceptualize the business ecosystem from the identity construct.

The purpose of this paper was to use visual and arc sensors to simultaneously obtain the underwater wet welding information, and a weld seam-forming model was made to predict the weld seam's geometric parameters. It is difficult to obtain a fine welding quality in underwater welding because of the intense disturbances of the water environment. To automatically control the welding quality, the weld seam-forming model should first be established. Thus, the foundation was laid for automatically controlling the underwater welding seam-forming quality.

Visual and arc sensors were used simultaneously to obtain the weld seam image, current and voltage information; then signal algorithms were used to process the information, and the back propagation (BP) neural network was used to model the process.

Experiment results showed that the BP neural network model could precisely predict the weld seam-forming parameters of underwater wet welding.

A weld seam-forming model of underwater wet welding process was made; this laid the foundation for establishing a controller for controlling the underwater wet welding process automatically.

This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.