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This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts. Varied studies relating to manufacturing and services sectors including healthcare, banking, information technology, power, education sector etc. stresses upon the systematic approach followed in applying the data analytical techniques; and also analyses how these techniques are effective in decision-making in different contexts. Especially, the application of regression modeling, financial modelling, multi-group modeling, cluster analysis, and sentiment analysis will help the readers in understanding critical business scenarios in the best possible way, and which later can help them in arriving at best solution for the business related problems. The individual chapters will help the readers in understanding the role of specific data analytic tools and techniques in resolving business operational issues experienced in manufacturing and service organisations in India and in developing countries.

The book offers a relevant resource that will help readers in the application and interpretation of data analytical statistical practices relating to emerging issues like customer experience, marketing capability, quality of manufactured products, strategic orientation, high-performance human resource policy, employee resilience, financial resources, etc. This book will be of interest to a professional audience that include practitioners, policy makers, NGOs, managers and employees as well as academicians, researchers and students.



Chapter 1. Business Analytics: Concept and Applications

The word business analytics has become a buzzword in the present era of experience economy. Primarily, the proliferation of the Internet and information technology has made business analytics a robust application area. On the other hand, it is equally impossible to deny its significant impact on the fields of information technology, quantitative methods and the decision sciences (Cegielski and Jones-Farmer 2016). Both industry and academia seek to hire talent in these areas with the hope of developing organizational competencies to sustain competitive advantage. Hopkins et al. (2007) and Hair et al. (2003) assert that adequate knowledge on business analytics techniques enables the analysts—practitioners, managers, etc—with capabilities that enable them to take quick and smart decisions and provide stable leadership to the organization to compete in the market effectively. On the other hand, it provides a platform for the researchers and academicians to lay down path for the theory development. However, Hawley (2016) pointed that business analytics focuses more on understanding the organizational culture than mere technology. Thus, for successful implementation and harnessing the benefits of business analytics the knowledge of an organization’s motivation, strengths and weaknesses is necessary (Hawley 2016).
Hardeep Chahal, Jeevan Jyoti, Jochen Wirtz

Chapter 2. Big Data Analytics: The Underlying Technologies Used by Organizations for Value Generation

The expansion of Internet and its applications globally has witnessed generation of high volume of data resulting in high volume of information. In the contemporary era of digital world, data is seen as the driving force behind the progression of business enterprises. Today, the data that is generated worldwide has grown ranging from terabytes to exabytes and petabytes, and the compounded rate of data further growing is much fast. The data generated widely has many forms and structures. The deluge of data generated, which is both valuable and challenging, along with emerging technologies and techniques that are used to handle it is referred to as the evolution and era of “Big Data”. As the big data is generated from multitudinous sources, majority of this data exists in unstructured form that demands specialized processing and storage capabilities, unlike the structured data that uses storage and processing of traditional relational structures. This results in high complexity and uncertainty in data. The usage of statistical analysis, computer-based models and quantitative methods that can help the business organizations to improve insights for better operations and decision-making is referred as business analytics. To work intelligently and focus on value generation, organizations need to focus on business analytics. The analytics are a critical component of big data computing. As defined in the literature, an intelligent enterprise has the characteristics similar to human nervous system and is responsive to external stimuli. To leverage the large volume of data for driving the business enterprises, timely and accurate insights derived out of the big data are a big challenge. The technologies like Hadoop and Apache Spark assist in handling big data on both fronts. However, handling and analysis of big data are a challenge for any organization with respect to its storage and technical expertise. Business analytics is used in business organizations for value generation by data manipulation along with business intelligence and report generation. Advanced analytics are also used by business enterprises that use techniques of data mining, data optimization and predictive forecasting.
Bhavna Arora

Chapter 3. Application of Panel Quantile Regression and Gravity Models in Exploring the Determinants of Turkish Automotive Export Industry

This paper purposes to determine potential factors influencing the amount of Turkish automotive industry exports. For this purpose, the available data of 68 major trading partners of Turkey in terms of automotive industry exports were utilized for the sample period 2007–2015. Both panel quantile regression and the gravity model of trade approaches were considered to analyze the relevant data. The empirical findings of this paper revealed that the population and the distance variables were found as statistically significant for all quantiles, while the former has positive and the latter has negative signs as expected. Results also indicated that there was a statistically significant positive correlation between GDP per capita and the amount of Turkish automotive industry exports at 10 and 50% quantiles; however, it was not statistically significant at 90% quantile despite its positive sign. Among Turkey’s exporter countries, being a EU member country dummy variable was found to have a statistically significant positive impact on the amount of automotive industry exports. Real exchange rate was not found as a significant determinant of the amount of automotive industry exports. In the lights of empirical evidence obtained from this study, several recommendations were made for Turkey’s future international trade policies.
Ibrahim Huseyni, Ali Kemal Çelik, Miraç Eren

Chapter 4. Impact of Macroeconomic and Bank-Specific Indicators on Net Interest Margin: An Empirical Analysis

The purpose of this paper is to identify the indicators from macroeconomic and bank environment, which tend to affect earning capacity (quantified by net interest margin) of public sector banks (PSBs) of India. The paper also quests to explore the possible linkages between the indicators under the purview of this paper. The financial statements, financial notes, and annual reports of the sample banks, publications from Government of India, Reserve Bank of India, and World Bank have been accessed to get the data regarding the variables under the study. The classical multiple regression analysis has been employed with diagnostic tests to derive concrete inferences from the data. The empirical evidences illuminated the positive correlation of gross domestic product (GDP), inflation, lending interest rate (LIR), and capital to risk-weighted assets ratio (CRAR) with the net interest margin (NIM) of sample banks, while as non-performing loans (NPLS) established an indirect relationship. The study established that favorable macroeconomic environment proves to be a main driver for encouraging net interest margin (NIM) with a prudent control over CRAR along with NPLs on the part of sample banks. The study suggested installing latest advances and practices of risk management especially on the credit front, which will also help the banks to utilize excessive capital rather than accumulating it unnecessarily. It is also suggested for the PSBs to merge for better consolidation, allocation of funds, and better investment prospects.
Arif Ahmad Wani, S. M. Imamul Haque, Shahid Hamid Raina

Chapter 5. A Trend Analysis of Reforms in the Indian Bond Market

The paper analyses the impact of various reforms undertaken by the government of india to improve liquidity, transparency, and security in the Indian bond market. It considers reforms initiated by government of india since 1992 that include introduction of system of primary dealers, establishment of Clearing Corporation of India Limited as a clearinghouse, introduction of screen-based trading in government securities through negotiated dealing system-order matching (NDS-OM), trading of bonds through stock exchanges, introduction of delivery versus payment system, etc. Time series graphs are used for analysis by collecting secondary data from Reserve Bank of India, Securities and Exchange Board of India, Clearing Corporation of India Limited, and National Stock Exchange. Indian government securities market has changed significantly in the last two decades. The impact of reforms on the Indian bond market is examined by analyzing the combined gross borrowing of center and state government through government securities (increased by around 8900% from 1991–92 to 2016–17), secondary market transactions in government securities (increased by around 430,000% from September 1994 to September 2017), net corporate debt outstanding (increased by around 225% from June 2010 to September 2017), total trade in corporate bond market (increased by around 1450% from 2007–08 to 2016–17), and other variables related to the liquidity and size of Indian bond market. The impact of reforms is found to be positive for all the dimensions but have significant impact only on the size and liquidity of the Indian bond market. The study concludes with strategic implications.
Rahul Rangotra

Chapter 6. Demand Forecasting of the Short-Lifecycle Dairy Products

Predictions of future market demands for dairy products are important determinants in developing marketing strategies and farm-production planning decisions. For business operations in dairy industry, the accuracy of the forecast is of crucial importance because of the volatile demand pattern, influenced by an environment of rapid and dynamic response. The current study aims to compare the forecasting models like moving average, regression, multiple regression, and the Holt–Winters model based on accuracy measures, applied to demand forecasting of a time series formed by a group of perishable dairy products in milk processing industry. Further, the metric analysis of various error-measuring techniques is also applied to select the least error-producing model for such products as a performance measure. Findings of the study will help dairy industry to achieve high order fill rate, good inventory control as well as high profits. However, the selection of these models depends upon the knowledge, availability of data, and context of forecasting.
Rahul S. Mor, Swatantra Kumar Jaiswal, Sarbjit Singh, Arvind Bhardwaj

Chapter 7. Customer Experience and Its Marketing Outcomes in Financial Services: A Multivariate Approach

The purpose of this paper is twofold: first, to validate the customer experience quality (EXQ) scale in Indian sector, across financial products in Indian settings. And second, to assess EXQ impact on the marketing outcomes, that is customer satisfaction, word-of-mouth, loyalty intentions and service value. The respondents comprised of customers of Jammu City, India, who have experienced one of the three services, that is Banking or Insurance or Investment from the public and private sectors. The customer experience quality scale is assessed through validity and reliability analysis assuring the validation of EXQ scale in Indian settings. It is validated as four-dimensional scale, that is peace of mind, moment of truth, outcome focus and product experience. Also, the findings suggest that all the four individual dimensions have positive and significant impact on the marketing outcomes. First, the study is based on three financial services such as banking, investment and insurance only, and for further research, it is suggested to adopt other services comprehensively to understand customer experience from their perspective. Secondly, the major limitation of the research is related to the presence of subjective responses of the customers with respect to customer experience constructs in the study. This study contributes to the extant marketing literature by validating the domain of consumer experience quality in financial service sector operating in emerging economies, that is India, and its impact on marketing outcomes.
Swati Raina, Hardeep Chahal, Kamani Dutta

Chapter 8. Re-investigating Market Orientation and Environmental Turbulence in Marketing Capability and Business Performance Linkage: A Structural Approach

This study aims to re-investigate the role of market orientation as an antecedent to marketing capability and effect of environmental turbulence as moderating variable in marketing capability—competitive advantage—business performance relationship. Data are collected from multiple respondents, that is, a branch manager and three senior managers of 144 branches of public and private banks operating in Jammu city, North India. The study establishes marketing capability as a three-dimensional construct, comprising outside-in, inside-out and spanning, unlike majority of previous studies on marketing capability. The study also supports the school of thought which believes that market orientation acts as an antecedent to marketing capability rather than its dimension. Further, the findings reveal partial mediating role of marketing capability on market orientation and competitive advantage linkage. However, environmental turbulence does not moderate in marketing capability-competitive advantage relationship in the tech-savvy banking sector.
Jagmeet Kaur, Hardeep Chahal, Mahesh Gupta

Chapter 9. Examining the Impact of Cultural Intelligence on Knowledge Sharing: Role of Moderating and Mediating Variables

Globalisation of world has brought lot of challenges for individuals and organisations in the form of cultural diversity management. In this perspective, cultural intelligence is an ability, which can enhance an employee’s skill to communicate with individuals belonging to his/her culture as well as host region nationals. The study aims at analysing the moderating role played by work experience between cultural intelligence (CQ) and cross-cultural adjustment (CCA) relationship. Further, the mediating role is played by cross-cultural adjustment between cultural intelligence and knowledge sharing relationship. 530 bank managers working in nationalised banks operating in Delhi (North India) have been contacted for the study. In order to establish normality of the data, 18 respondents have been deleted by inspecting boxplots. Therefore, the effective sample came to 512. Confirmatory factor analysis (CFA) has been used to validate the scale, and to check the hypotheses, structural equation modelling (SEM) has been used. The result reveals that work experience moderates between CQ and CCA. The findings further reveal that CCA mediate between CQ and knowledge sharing relationship. The study is cross-sectional in nature. Further, the role of only one moderating variable, i.e. work experience, has been explored between CQ and CCA relationship. The study contributes towards cultural intelligence theory. Cultural intelligence acts as an essential tool in selection of managers who can work effectively in cross-cultural context. Culturally intelligent managers are talented and interactive which helps them to give their best performance. These managers can be sent for overseas assignments as they are able to communicate successfully with individuals belonging to dissimilar cultural backgrounds.
Jeevan Jyoti, Vijay Pereira, Sumeet Kour

Chapter 10. Employer Branding Analytics and Retention Strategies for Sustainable Growth of Organizations

Disruptive trends continue to create opportunities for organizations to quickly develop new capabilities and gain a competitive advantage. Employer branding and organizational attractiveness have garnered considerable research attention over the years owing to their significance in disruptive economy. Digitalization, global development, technological advancements, and greater dependence on data analytics have significantly accelerated market disruption, causing difficulties for employers in attracting employees in competitive advantages. For organizations, it is necessary to remain competitive; to this end, employers do a number of exercises to retain and attract employees. The aim of the research paper empirically explores the impact of organization’s branding on employer attractiveness in Indian companies. Thus, 300 employees employed in various companies in India were surveyed. This paper uses correlation technique, factor analysis, and stepwise regression techniques to establish the impact of employer branding analytics on organizational attractiveness. Results suggest that branding analytics positively and significantly relates to companies’ attractiveness. This paper offers deeper insights into the link between both of the variables, makes association between aspects and dimensions of the aforementioned constructs, and in doing so, provides significant implications for both researchers and practitioners. Findings of the study could help practitioners identify employer branding dimensions influencing organizational attractiveness the most. Practitioners could, with such knowledge, incorporate the most influential dimensions of employer branding in organizational culture.
Ravindra Sharma, S. P. Singh, Geeta Rana

Correction to: Customer Experience and Its Marketing Outcomes in Financial Services: A Multivariate Approach

Correction to: Chapter “Customer Experience and Its Marketing Outcomes in Financial Services: A Multivariate Approach” in H. Chahal et al. (eds.), Understanding the Role of Business Analytics, https://​doi.​org/​10.​1007/​978-981-13-1334-9_​7
Swati Raina, Hardeep Chahal, Kamani Dutta
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