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The purpose of this paper is to identify and analyze various critical success factors (CSFs) that can facilitate smartphone manufacturing in India. This paper further aims to understand the mutual interactions among these CSFs through identification of the hierarchical relationships among them.

A framework for a smartphone manufacturing system has been developed, wherein the hierarchical inter-relationships between identified CSFs have been presented and interpreted using total interpretive structural modeling (TISM). Cross-impact matrix multiplication applied to classification analysis has been further employed to identify the driving power as well as dependence power of these CSFs.

In the present research, 15 CSFs have been identified through literature review and expert opinions. The hierarchical framework developed using TISM has revealed the inter-dependencies among these CSFs. This research further categorizes CSFs into three clusters. The first cluster comprises of CSFs having high dependence power, the second cluster identifies CSFs having high driving power and the third cluster identifies CSFs which act as linkages between the driver CSFs and dependent CSFs.

This study has implications for both practitioners and academia. It provides a comprehensive list of CSFs that are relevant to develop a smartphone ecosystem in India. In addition, this study will help decision makers to strategically focus on the main drivers of the ecosystem that requires the immediate attention of decision makers. The methodology employed in this study provides a mechanism to conduct an exploratory study by identifying the factors and analyzing their interactions through the development of a hierarchical framework.

The proposed framework developed through qualitative modeling is an effort to understand relevant factors that can promote the smartphone manufacturing ecosystem. This study makes a significant contribution in the literature of smartphone manufacturing, which captures the perspective of different stakeholders.

The purpose of this paper is to discuss sentiment search, which not only retrieves data related to submitted keywords but also identifies sentiment opinion implied in the retrieved data and the subject targeted by this opinion.

The authors propose a retrieval framework known as Cross-Domain Sentiment Search (CSS), which combines the usage of domain ontologies with specific linguistic rules to handle sentiment terms in textual data. The CSS framework also supports incrementally enriching domain ontologies when applied in new domains.

The authors found that domain ontologies are extremely helpful when CSS is applied in specific domains. In the meantime, the embedded linguistic rules make CSS achieve better performance as compared to data mining techniques.

The approach has been initially applied in a real social monitoring system of a professional IT company. Thus, it is proved to be able to handle real data acquired from social media channels such as electronic newspapers or social networks.

The authors have placed aspect-based sentiment analysis in the context of semantic search and introduced the CSS framework for the whole sentiment search process. The formal definitions of Sentiment Ontology and aspect-based sentiment analysis are also presented. This distinguishes the work from other related works.

The purpose of this paper is to analyze the inverted U-shaped relationship between external search in the collaboration network and firm innovation outcomes. It also seeks to explore whether these curvilinear relationships are moderated by the network centrality and structural holes in the knowledge network.

In this empirical research, the authors collected a sample of patents in the smartphone industry over the period of 2000-2017. Then the authors examined the direct roles of external search breadth and depth in the collaboration network and the moderating role of network embeddedness in the knowledge network by using negative binomial regression.

Results found that external search in the collaboration network contributes more to firm innovation outcomes when the breadth and depth of the external search are moderate rather than high or low. Furthermore, both network centrality and structural holes in the knowledge network have positive effects on the external search breadth – innovation outcomes and external search depth – innovation outcomes relationships.

The authors collected the patent data within the single industry and excluded other types of industries. This may limit the generalization of the findings.

The paper has practical implications for adopting appropriate search strategies in the collaboration network and developing a better understanding of the effect of network embeddedness in the knowledge network on firm innovation outcomes. The findings suggest future directions for technology-intensive industries to improve their innovation output.

This study adds value to open innovation literature by pointing out a curvilinear relationship (inverted U-shaped) between external search breadth/depth and innovation outcomes in collaboration networks, in contrast to studies focused on firms’ external collaboration strategies in a certain industry context. Furthermore, this study reinforces the key contingent role of embeddedness in knowledge networks. This study provides a valuable theoretical framework of innovation outcome determinants by connecting the network perspective of open innovation theory with an embeddedness view.

This paper aims to propose the following questions: How do structural network embeddedness influence firms’ incremental innovation capability? Does technology cluster moderate the relationships between them?

In this empirical research, the authors collected a sample of patent data in the smartphone industry over the period of 2000-2018. Then, the authors examined the direct roles of structural network embeddedness on firms’ incremental innovation capability and the moderating role of technology cluster by using ordinary linear squares regression.

The empirical results show that occupying the central position positively affects firms’ incremental innovation capability, and clustering strengthens this linear relationship. Furthermore, bridging structural holes has an inverted U-shaped effect on incremental innovation capability, and clustering positively moderated this nonlinear relationship, while bridging ties across different clusters plays a negative moderation role in this relationship.

This empirical research provides new insights into whether and how firms can grasp the benefits of structural network embeddedness to conduct incremental innovations and the moderation effects of technology cluster contingencies. It further contributes to the structural network embeddedness–incremental innovation capability issue by extending its research context to the smartphone industry.

This paper provides the strategic direction and coordination mechanism selection for the intelligent transformation of manufacturing enterprises.

A theoretical framework is developed through grounded theory and case analysis.

Collaboration value is the building block of the intelligent product ecosystem. The ecosystem is upgraded via a path of product coordination, platform coordination and network coordination.

This paper provides a framework for enterprises to build an intelligent product ecosystem.

The proposed intelligent product ecosystem framework is new to the literature and lays down a fruitful avenue for future research.

Previous studies examined the effect of inter-organizational collaboration relationships on organizational innovation. However, most focused on the configuration of the network from the static network perspective, and few examined the influence of network structure stability on an organization's exploratory innovation from the ego-network perspective. This study addresses this research gap by focusing on ego-network stability and its effect on an organization's exploratory innovation.

The empirical setting is the smartphone collaboration network from 2004 to 2017. We selected one-site schemes and panel data of patents from the Derwent Innovation Database. A negative binomial model with fixed effects was used to test our hypotheses.

The regression results show that an organization's ego-network stability has an inverted-U-shaped relationship with its exploratory innovation. Global cohesion of the focal organization's knowledge network moderates the process in such a way that when it is at a high level, an organization's exploratory innovation can benefit more from a moderate level of ego-network stability. However, local cohesion moderates in such a way that, at a low level, an organization's exploratory innovation can benefit more from a moderate level of ego-network stability.

This study highlights the importance of ego-network stability and its effect on the focal organization's exploratory innovation. It contributes to the literature on the relationship between ego-network stability and exploratory innovation by investigating the moderating role of global cohesion and local cohesion in knowledge networks.

Organizations are being compelled to revamp their loyalty programs due to the increase in digital transactions, customer acquisition costs and competition in the loyalty market. Given the significance of consumer-brand relationships, businesses must quickly identify the relationships that best elicit brand loyalty. Thus, this study seeks to develop a comprehensive model about the consumer-brand relationship that encompasses the following constructs: brand trust, brand satisfaction, brand preference, brand affect, brand equity, brand image, commitment, variety seeking, and relationship length, and their influence on brand loyalty. The study also investigates the impact of the bandwagon effect, in tandem with the aforesaid antecedents.

A data set comprising 248 consumers in India was used to validate the measures and test the hypotheses. Structural equation modeling was employed to test the hypothesis. The data analysis was carried out on R version 4.0.2.

The study found that all the selected constructs exert influence on brand loyalty, although commitment, brand equity and brand preference exhibited the strongest impact. The bandwagon effect also demonstrated a strong effect.

This study advances the field's understanding of information processing through a consolidated meta-view of various consumer-brand relationship constructs along with bandwagon effects. Perhaps the most important contribution is shedding light on the influence of bandwagon effects on brand loyalty.

The theory of dynamic capabilities (DC) was originally proposed as an improved alternative to the existing resource-based view theory of strategy to address the issue of renewing competences in fast changing environments. However, in an era of transition, how will the theory address the multiple challenges arising on technology, social and energy regime front? The paper aims to address this issue.

This paper takes the approach of theoretical proposition building, supported by real-life examples.

Findings include a set of managerial practices that will help building DCs in rapidly changing environments.

The theoretical propositions offer further scope of research for other scholars to test and build the theory further.

The interplay of three forces outlined in the paper has significant strategic implications for firms.

The paper proposes a framework called deep thinking which has not been proposed before and which particularly addresses how firms can meet the challenge of transitioning into a new era with the help of this framework.

The purpose of this study is to determine the factors that underpin consumer switching intention in the smartphone industry. Most of the literature on brand switching uses conventional models that lack the ability to explain this behavior for high-technology products. Such products have unique characteristics that make the switching process more challenging from the consumer perspective.

The proposed model is built based on the related theories that consider the distinctive aspects of high-technology products. Furthermore, two variables “relative advantage of product features” and “company innovativeness” are introduced for the first time to evaluate consumer attitude to switch a high-technology product. The smartphone industry was selected to test the proposed model, where an online survey was sent to Apple and Samsung users.

The results confirm the expectation that perceived product usefulness, perceived ease of use and relative advantage of product features are the major factors driving the intention of users to switch, whereas subjective norms have limited impact. The financial cost of switching is the main barrier to consumers’ decision to switch to a new technology. The pleasure consumers feel toward their brand and the other brand is positively associated with their attitude toward switching.

This research contributes to the literature on brand switching by introducing a comprehensive model that explains consumer switching behavior of high-technology products. Research findings would allow managers to draft better marketing strategies to improve consumer brand awareness.

The majority of literature on brand switching uses simple models to explain consumer behavior. This study is the first attempt to build a comprehensive model that considers the characteristics of high-technology products and how they shape consumer behavior during the decision-making process.

The purpose of this study is to identify and characterize the role of both original equipment manufacturer (OEM) and module supplier (MS) knowledge in the smartphone industry. In particular, this study aims to evaluate which of the two actors possesses the knowledge that has the greatest impact on the market satisfaction.

This study explores and combines the concepts of modularity and knowledge management by investigating the patent portfolio of 16 leading smartphone OEMs and 144 MSs. The applied methodology is based on the content analysis of patent data to extract information on both OEM’s and MS’s component knowledge.

The results show that, although its components are purchased from external MSs, the OEM should preserve both a general and specific concentration of component knowledge, as well as on the end product, to achieve a greater market satisfaction. Moreover, a positive direct relationship was found for the MS between the general concentration of component knowledge and the market satisfaction.

The novelty of this study is to segment the knowledge of both the OEM and the MS on multiple levels. To the best of the authors’ knowledge, this is one of the first studies that investigates the end product and component knowledge of both actors by filtering patent data using text-mining techniques. The originality of this work is to intercept the relationship between the different shades of knowledge of each actor and the market satisfaction.