Achieving superior organizational performance via big data predictive analytics: A dynamic capability view

The art of unwinding voluminous data expects the expertise in analyzing meaningful decisions out of the acquired information. To encounter new age challenges, practitioners are trying hard to shatter the constraints and work edge-to-edge to achieve higher performance (Market, Financial and Operational performance). It is evident that organizations desire to exploit maximum of their injected resources, but often fail to reap their actual potential. Developing resource-based capabilities stands out to be the most concerned aspect for the firms in recent times, and the same is studied by the previous scholars. In the dearth of literature, it is challenging to find out evidence which marks up the effect of strategic resources in the development of dynamic organizational capability. This study is a two-fold attempt to examine the relationship between organizational capabilities, i.e. big data predictive analytics while achieving superior organizational performance; also, examining the effect of control variables on superior organizational of performance. We tested our research hypotheses using cross-sectional data of 209 responses collected using pre-tested single-informant questionnaire. The results underpin criticality human factor while developing analytical capabilities dynamic in nature in the process of achieving superior performance.     

Customer involvement in big data analytics and its impact on B2B innovation

Extant literature assumes that customers mainly serve as passive data providers and that firms take responsibility for big data analytics. In line with a current trend in real-world practice, this research, based on the open innovation literature, challenges this assumption and argues that customers can have more engagement in big data analytics. The authors distinguish two constructs: Customer as Data Provider (CDP) and Customer as Data Analyst (CDA). The former is consistent with the mainstream view that customers serve as the data source. The latter, on the other hand, sheds light on an active role customers play in big data analytics – that is, customers participate in a co-creation process where they acquire, analyze and act on big data. Using survey data of 148 Business-to-Business (B2B) innovation projects, the authors find that both types of customer involvement facilitate B2B product innovation. Furthermore, the authors examine moderation effects of customer need tacitness and customer need diversity. Results show that customer need tacitness negatively moderates the relationship between CDP and new product performance while customer need diversity yields a positive moderation effect. Customer need tacitness is also found to positively moderate the relationship between CDA and new product performance.     

Social and organizational capital: Building the context for innovation

In the light of the key role intellectual capital has for firms' innovation capability, this paper analyzes the influence of two of their dimensions, organizational capital and social capital, on firms' product innovation, and the moderating role of radicalness. Unlike previous studies, the unit of analysis will not be the firm, but the R&D department. Thus, our research, conducted with a sample of Spanish industrial companies, provides a new insight with interesting results. First, our findings show that social capital favours firms' product innovation, especially under radical innovations. Second, organizational capital has an indirect effect on product innovation through positive influence on social capital. This implies that firms can stimulate communication and interaction among people, and therefore innovative activity, by means of explicit and codified knowledge (organizational capital).     

Product–service innovation and performance: the role of collaborative partnerships and R&D intensity

Treating the intersection of the strategic partnerships, R&D intensity and servitisation literatures, this study explores empirically whether external collaborative service development and provision and industrial R&D intensity help to unpack the complex relation between product–service innovation (servitisation) and performance. We argue that manufacturing firms implementing services benefit from strategic partnerships with Knowledge‐Intensive Business Service (KIBS) firms. KIBS partnering provides opportunities for downsizing, externalising risks and sharing knowledge. Additionally, manufacturers in R&D‐intensive industries are more likely to benefit from implementing service provision than firms in other sectors because of industry dynamics and reduced customer uncertainty. The study surveys executives in 370 large manufacturers worldwide. Results reinforce the importance of concentric strategic partnerships to successful product–service innovation in high R&D industries.     

Big data analytics for supply chain relationship in banking

This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore the internal B2B data to improve supply chain finance and the efficiency of marketing tactics and campaigns. A case study was conducted by analyzing two types of supply chain relationships: (1) supply chain relationships in the credit reports; (2) e-wiring transactions among supply chain companies. The results show that big data analytics is very useful in terms of improving the commercial banks' marketing and risk management performances. The case study also set a good example for B2B firms seeking to understand how they could leverage big data analytics to differentiate customer solutions, sustain profitability and generate new business values. Theorical and practical implications are also discussed.     

B2B analytics in the airline market: Harnessing the power of consumer big data

This paper utilizes market-level data to explore the relative performance of individual companies amongst defined competitors. We show the potential of using consumer clickstream data, an important type of big data, to create a new set of B2B analytical frameworks. In the markets where complex interactions between competitors, search intermediaries and consumers create a network, B2B relationships can be inferred from consumer search patterns, and can then be modeled to gauge the online performance. A commercial dataset from ComScore’s US panel of one million users is used to illustrate a new approach to measure and evaluate the online performance of competitors in the US airline market. The methodology and associated performance framework demonstrate the potential for new forms of market intelligence based on the visualization of market networks, online performance calculated from matrix algorithms, the measurement of the impact of search intermediaries, and the identification of latent relationships. This research makes theoretical and empirical contributions to the debate on the use of big data for B2B market analytics. B2B managers can use this approach to extend their network horizon from an egocentric to a network view of competition and map out their competitive landscape from the perspective of the customer.     

The diffusion of an organizational innovation: International data telecommunications and multinational industrial firms

The paper analyses the structural and technological determinants of the diffusion of international data network as a major technological and organizational innovation in a sample of 40 U.S. and European multinational firms in the period 1963–1980. According to the results faster adopters appeared to be large U.S. firms, exposed to worldwide competition, with inhouse telecommunication skills. Smaller European firms adopted the technology later, often pushed by the provision of ad hoc technical solutions by service and hardware marketing firms. Smaller latecomers with centralized management structures were, however, quicker in the diffusion process. Both in the interfirm and intrafirm diffusion ‘implicit knowledge’ was a more effective factor than R–D intensity.     

Role of big data and social media analytics for business to business sustainability: A participatory web context

The digital transformation is an accumulation of various digital advancements, such as the transformation of the web phenomenon. The participatory web that allows for active user engagement and gather intelligence has been widely recognised as a value add tool by organisations of all shapes and sizes to improve business productivity and efficiency. However, its ability to facilitate sustainable business-to-business (B2B) activities has lacked focus in the business and management literature to date. This qualitative research is exploratory in nature and fills this gap through findings arising from interviews of managers and by developing taxonomies that highlight the capability of participatory web over passive web to enable different firms to engage in business operations. For this purpose, two important interrelated functions of business i.e. operations and marketing have been mapped against three dimensions of sustainability. Consequently, this research demonstrates the ability of big data and social media analytics within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities. The research findings will be useful for both academics and managers who are interested in understanding and further developing the business use of participatory web tools to achieve business sustainability. Hence, this may be considered as a distinct way of attaining sustainability.     

An empirical case study on Indian consumers' sentiment towards electric vehicles: A big data analytics approach

Today, climate change due to global warming is a significant concern to all of us. India's rate of greenhouse gas emissions is increasing day by day, placing India in the top ten emitters in the world. Air pollution is one of the significant contributors to the greenhouse effect. Transportation contributes about 10% of the air pollution in India. The Indian government is taking steps to reduce air pollution by encouraging the use of electric vehicles. But, success depends on consumer's sentiment, perception and understanding towards Electric Vehicles (EV). This case study tried to capture the feeling, attitude, and emotions of Indian consumers' towards electric vehicles. The main objective of this study was to extract opinions valuable to prospective buyers (to know what is best for them), marketers (for determining what features should be advertised) and manufacturers (for deciding what features should be improved) using Deep Learning techniques (e.g Doc2Vec Algorithm, Recurrent Neural Network (RNN), Convolutional Neural Network (CNN)). Due to the very nature of social media data, big data platform was chosen to analyze the sentiment towards EV. Deep Learning based techniques were preferred over traditional machine learning algorithms (Support Vector Machine, Logistic regression and Decision tree, etc.) due to its superior text mining capabilities. Two years data (2016 to 2018) were collected from different social media platform for this case study. The results showed the efficiency of deep learning algorithms and found CNN yield better results in-compare to others. The proposed optimal model will help consumers, designers and manufacturers in their decision-making capabilities to choose, design and manufacture EV.     

Recombination for innovation: performance outcomes from international partnerships in China

This paper examines the relationship between different types of international partnerships and innovation performance. By drawing on a conceptual framework which outlines how new bundles of transferrable and nontransferrable ownership advantages are created from such partnerships (Collinson and Narula, 2014 ), we analyze empirical evidence from a large‐scale survey of 320 individual company responses from the China‐based operations of foreign multinational firms alongside in‐depth case studies. Our study reveals that different types of collaborative partnerships (cooperative vs. competitive) are associated with different innovation performance outcomes (product vs. process innovation). In addition, we find that a sustainable, reciprocal relationship between collaborative partners can generate superior innovation performance. Contextual factors including the role of government and industry characteristics have an important bearing on innovation performance in collaborative partnerships in China. We conclude with implications for researchers, managers, and policymakers.     

The field of radical innovation: Making sense of organizational cultures and radical innovation

Organic organizational structures and cultures facilitate innovation because they allow organizations to shift their understanding of what a product, service or technology means. Yet, organic organizations may have to instill mechanistic structures and bureaucratic processes if they produce successful radical innovations. Thus, the basis of innovation can be undermined by its consequences. To explore this issue, this paper analyzes data from an ongoing longitudinal case study of a SME digital-design agency that developed a radical innovation for the market research industry. The paper observes that founders of the organization shifted their position to become managers as a result of their radical innovation and that other members of the organization have, consequently, re-evaluated their attitude toward the organization. To conceptualize our findings we turn to the work of Pierre Bourdieu. His notion of fields—which structure experiences and are, themselves, structured by experiences—offers a framework to understand the dynamics within an organization that occur as a result of a successful radical innovation. The contribution of our paper is: theoretically, we relate the discussion of innovation to wider social theories of practice and, thus, introduce temporal and cultural dynamics into the account of radical innovation; methodologically, we provide an example of a longitudinal study; and, in managerial terms, we indicate where divisions occur within an organization concerning the construction of meaning between managers and employees after a radical innovation.     

A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making

User-generated content about brands is an important source of big data that can be transformed into valuable information. A huge number of items are reviewed and rated by consumers on a daily basis, and managers have a keen interest in real-time monitoring of this information to improve decision-making. The main challenge is to mine reliable textual consumer opinions, and automatically use them to rate the best products or brands. We propose a framework to automatically analyse these reviews, transforming negative and positive user opinions in a quantitative score. Sentiment analysis was employed to analyse online reviews on Amazon. The Fake Review Detection Framework—FRDF— detects and removes fake reviews using Natural Language Processing technology. The FRDF was tested on reviews of products from high-tech industries. Brands were rated according to consumer sentiment. The findings demonstrate that brand managers and consumers would find this tool useful, in combination with the 5-Star score, for more comprehensive decision-making. For instance, the FRDF ranks the best products by price alongside their respective sentiment value and the 5-Star score.     

Innovating the innovation process: an organisational experiment in global pharma pursuing radical innovation

The challenge of managing the fuzzy front end of the innovation process is particularly acute for large, multi‐brand, research and development (R&D)‐intensive firms. Poor performance at generating radical innovations has resulted in many large organisations seeking to innovate how they organise for innovation. This paper presents an inductive, longitudinal study of an organisational experiment that sought to get ‘game‐changing, radical ideas’ into the new product development funnel of a top three pharma. The immediate outcomes of a team‐based internal innovation tournament included 33 new product ideas, 14 of which were radical. The medium term outcome of the experiment was a reorganisation of how the firm now pursues radical innovation activities. We link these outcomes to team leadership, contrasting innovation processes, including decisions about how to incorporate the ‘voice of the consumer’. The inductive, longitudinal study suggests causal interconnections between innovation team leadership, innovation team processes, and innovation outcomes.     

Client dependence and vendor innovation: The moderating role of organizational culture

With the dramatic increase in technological interconnectedness between firms and the overall speed of technological change, organizations depend on each other to survive and stay competitive. While it is generally believed that dyads and networks can offer advantages over internal development in the innovation process, the authors suggest that it is not necessarily the case. Using a sample of 120 vendor firms that work in information technology industries in the Indian subcontinent, they find that client dependence in the inter-organizational relationship decreases vendor innovation. To resolve this dark side of business relationships, they further examine how the organizational culture can impact the dependence-innovation relationship. In line with organization literature, the authors distinguish two sub-dimensions of outcome-oriented culture: performance orientation, which reflects a firm's internal focus on employee performance, and competitiveness, which reflects a firm's focus on external competitors and markets. It is found that a vendor's competitiveness facilitates innovation, and that it weakens the negative effect of client dependence on vendor innovation. However, performance orientation strengthens the negative effect of client dependence on vendor innovation. Accordingly, in order to prevent themselves from falling into the dependence trap in the innovation process, firms need to build an externally oriented competitive culture and avoid overemphasizing their internal performance.     

Leadership and organizational learning's role on innovation and performance: Lessons from Spain

Leadership style has been traditionally emphasized as one of the most important individual influences on firm innovation. Scholars are now paying growing attention to the possibility that the collective capability of organizational learning plays a key role in determining innovation. We propose that leadership style, an individual feature, and organizational learning, a collective process, simultaneously and positively affect firm innovation. A structural equation model and data from 408 large firms in four sectors supported our hypotheses. Organizational learning had a stronger direct influence on innovation than CEO transformational leadership for our sample; however, leadership had a strong, significant influence on organizational learning, indirectly affecting firm innovation. Additionally, innovation positively and significantly influenced performance. Organizational learning also positively affected performance, but interestingly mainly through innovation.     

Joint problem solving and organizational learning capacity in new product innovation

There is a growing need for firms to acquire knowledge externally, but the process has become increasingly complicated. This article studies the mediating roles of the three process dimensions of organizational learning capacity (OLC), namely, knowledge acquisition, transformation, and application capabilities, in the context of a joint problem solving (JPS) arrangement with external collaborators for new product innovation. They employed the structural equation modelling method and analyse a sample of 331 high-tech manufacturers in China. Their results supported a conceptual model that shows (i) JPS exerts a positive impact on knowledge acquisition and transformation capabilities; (ii) these two capabilities promote knowledge application capacity; (iii) knowledge acquisition alone, and the combination of application and transformation capabilities, mediate the effect of JPS on both innovation efficacy and efficiency. Knowledge acquisition and application capabilities also jointly mediate the effect of JPS on innovation efficacy. They added to the existing literature by highlighting the need to consider the mediating roles of different OLC dimensions and the external context of JPS for learning capacity acquisition. Our model provides a practical framework for managers to better understand and influence OLC dimensions to improve innovation when engaging in JPS.     

Commercialization performance of outbound open innovation projects in public research organizations: The roles of innovation potential and organizational capabilities

The current literature on open innovation (OI) has been limited to organization-level studies of inbound OI despite the importance of understanding outbound OI to improve performance of public research organizations (PRO) at project level. Our study contributes to the OI literature by investigating the relationship between the innovation potential and the commercialization performance of 189 outbound OI projects between PROs and firms, and the effect of network and project management processes on this relationship. In line with our expectation, our results demonstrate that PRO-firm outbound OI projects with technologies of high innovation potential are likely to have high commercialization performance. In addition, we empirically establish that among projects with technologies of high innovation potential, those with high resource allocation quality are more likely to have high commercialization performance. Finally, our findings indicate that among projects with technologies of high innovation potential, those with high opportunity discovery through networks are more likely to have high commercialization performance.     

Complementarity in product,process, and organizational innovation decisions: evidence from European firms

This work uses a sample of firm-level data from seven EU countries to explore the possible roles of simultaneity and heterogeneity in determining firms' decisions to engage in three types of innovation. Process, product, and organizational innovations are considered jointly, by applying a multivariate probit specification. The results support the hypothesis that the three innovation decisions are interdependent. This has straightforward implications for the practice of R&D managers. In order to gain advantages from an innovation, innovation managers need to jointly exploit these different types of innovation activities and their potential synergies. Given that the innovative firms in the sample, desire additional credit which actually they do not obtain, R&D managers should also be concerned with the financing sources firms have access to. Finally, from the analysis it also emerges that public support boost all the three forms of innovation.     

Vertical innovation partnerships and relational performance: The mediating role of trust,interdependence, and familiarity

Which relational atmosphere would allow clients and suppliers to fully benefit from their innovation partnerships? Adopting an interactionist approach, we hypothesized that elements of a partnership atmosphere mediate the relationship between partnership type and relational performance. Based on taxonomic analysis of 160 cross-industry vertical innovation partnerships (VIPs) with differing contractual, relational, and organizational arrangements, we identified four VIP types: free, project-based, elaborated, and exclusive. Our results did not support a direct effect from VIP types on performance. However, we found that a trustful atmosphere enables achieving and exceeding expected benefits in both project-based and exclusive VIPs, whereas a familiar atmosphere enables achieving and exceeding expected benefits only for exclusive VIPs, and interdependence allows exceeding benefits only for project-based VIPs.     

Multidimensional latent traits of perceived organizational innovation: Differences between Thai and Egyptian employees

A new approach, the multidimensional latent regression (MLR) approach of item response theory, is employed to evaluate the dimensions of individual employee creativity, workplace atmosphere, and workplace innovative activity. Based on the MLR concept, the relationships among the measurement scales of these variables are tested for their unidimensionality versus multidimensionality. Multidimensionality was found. While workplace atmosphere is closely linked to workplace innovative activity, individual employee creativity forms its own dimension but is still positively linked to the other two measures. To achieve an accurate comparison between the two groups of Thai and Egyptian employees who have the same levels of agreement with the scale items, it is necessary to adjust the scores of Egyptian employees downwards.