Understanding market agility for new product success with big data analytics

Abstract The complexity that characterises the dynamic nature of the various environmental factors makes it very compelling for firms to be capable of addressing the changing customers' needs. The current study examines the role of big data in new product success. We develop a qualitative research with case study approach to look at this. Specifically, we look at multiple cases to get in-depth understanding of customer agility for new product success with big data analytics. The findings of the study provide insight into the role of customer agility in new product success. This study unpacks the interconnectedness of the effective use of data aggregation tools, the effectiveness of data analysis tools and customer agility. It also explores the link between all of these factors and new product success. The study is reasonably telling in that it shows that the effective use of data aggregation and data analysis tools results in customer agility which in itself explains how an organisation senses and responds speedily to opportunities for innovation in the competitive marketing environment. The current study provides significant theoretical contributions by providing evidence for the role of big data analytics, big data aggregation tools, customer agility, organisational slack and environmental turbulence in new product success.

[1]  Stanley Kam Sing Wong,et al.  Impacts of environmental turbulence on entrepreneurial orientation and new product success , 2014 .

[2]  Sharan B. Merriam,et al.  Qualitative research and case study applications in education , 1998 .

[3]  Canon Tong,et al.  The influence of market orientation on new product success , 2012 .

[4]  K. Atuahene–Gima,et al.  Resolving the Capability–Rigidity Paradox in New Product Innovation , 2005 .

[5]  A. Strauss,et al.  The discovery of grounded theory: strategies for qualitative research aldine de gruyter , 1968 .

[6]  J. Rojo-álvarez,et al.  Using big data from Customer Relationship Management information systems to determine the client profile in the hotel sector , 2018, Tourism Management.

[7]  Douglas J. Ayers,et al.  An Exploratory Investigation of Organizational Antecedents to New Product Success , 1997 .

[8]  Weiguo Fan,et al.  Measuring Customer Agility from Online Reviews Using Big Data Text Analytics , 2018, J. Manag. Inf. Syst..

[9]  A. Gbadamosi.  Exploring the growing link of ethnic entrepreneurship, markets, and Pentecostalism in London (UK): An empirical study , 2015 .

[10]  Brent Kitchens,et al.  Advanced Customer Analytics: Strategic Value Through Integration of Relationship-Oriented Big Data , 2018, J. Manag. Inf. Syst..

[11]  Ai-Hsuan Chiang,et al.  Network agility as a trigger for enhancing firm performance: A case study of a high-tech firm implementing the mixed channel strategy , 2011 .

[12]  S Cavanagh,et al.  Content analysis: concepts, methods and applications. , 1997, Nurse researcher.

[13]  Chaoqun Ma,et al.  The effect of strategic alliance resource accumulation and process characteristics on new product success: Exploration of international high-tech strategic alliances in China , 2012 .

[14]  J. Amankwah‐Amoah,et al.  Bridging technology divide to improve business environment: Insights from African nations , 2019, Journal of Business Research.

[15]  Kathleen M. Eisenhardt,et al.  DYNAMIC CAPABILITIES, WHAT ARE THEY? , 2000 .

[16]  E. Guba,et al.  Paradigmatic Controversies, Contradictions, and Emerging Confluences. , 2005 .

[17]  Lerzan Aksoy,et al.  Customer Engagement in a Big Data World , 2016 .

[18]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[19]  P. Eriksson,et al.  Qualitative Methods in Business Research , 2008 .

[20]  Sabine Kuester,et al.  The catbird seat of the sales force : how sales force integration leads to new product success , 2017 .

[21]  Christopher G. Reddick,et al.  Customer agility and responsiveness through big data analytics for public value creation: A case study of Houston 311 on-demand services , 2018, Gov. Inf. Q..

[22]  Venkatesh Shankar,et al.  Effective Marketing Science Applications: Insights from the ISMS-MSI Practice Prize Finalist Papers and Projects , 2013, Mark. Sci..

[23]  M. Patton.  Two Decades of Developments in Qualitative Inquiry , 2002 .

[24]  E. Guba.  Criteria for assessing the trustworthiness of naturalistic inquiries , 1981 .

[25]  Susan Spiggle.  Analysis and Interpretation of Qualitative Data in Consumer Research , 1994 .

[26]  Xavier Brusset,et al.  Does supply chain visibility enhance agility , 2016 .

[27]  Parsuram Nayak,et al.  Application of Statistical Tools for Data Analysis and Interpretation in Rice Plant Pathology , 2018 .

[28]  Eric T. Bradlow,et al.  The Role of Big Data and Predictive Analytics in Retailing , 2017 .

[29]  M. Christopher,et al.  Measuring agile capabilities in the supply chain , 2001 .

[30]  Matthew B. Miles,et al.  Qualitative Data Analysis: An Expanded Sourcebook , 1994 .

[31]  Jan Löwstedt,et al.  Managing asset orchestration: A processual approach to adapting to dynamic environments , 2018, Journal of Business Research.

[32]  Dae Ryun Chang,et al.  Organizational memory influences new product success , 2008 .

[33]  Kim Hua Tan,et al.  Unlocking the power of big data in new product development , 2016, Annals of Operations Research.

[34]  John D'Ambra,et al.  Analyzing consumer goal structure in online group buying: A means-end chain approach , 2017, Inf. Manag..

[35]  C. Wang.  Guanxi vs. relationship marketing: Exploring underlying differences , 2007 .

[36]  Belle Selene Xia,et al.  Review of business intelligence through data analysis , 2014 .

[37]  Azeddine Bilami,et al.  Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks , 2018, IEEE Access.

[38]  Juneho Um,et al.  Improving supply chain flexibility and agility through variety management , 2017 .

[39]  Varun Grover,et al.  Investigating firm's customer agility and firm performance: The importance of aligning sense and respond capabilities , 2012 .

[40]  Dirk Berg-Schlosser,et al.  Comparative Research Design: Case and Variable Selection , 2009 .

[41]  M. Christopher,et al.  An Integrated Model for the Design of Agile Supply Chains. , 2001 .

[42]  Dapeng Wu,et al.  Scalable privacy-preserving big data aggregation mechanism , 2016 .

[43]  Jiangang Shu,et al.  Privacy-Preserving Data Aggregation against False Data Injection Attacks in Fog Computing , 2018, Sensors.

[44]  Nagesh N. Murthy,et al.  Achieving supply chain agility through IT integration and flexibility , 2008 .

[45]  Scott B. Friend,et al.  Big Data Facilitation, Utilization, and Monetization: Exploring the 3Vs in a New Product Development Process , 2017 .

[46]  Christopher L. Tucci,et al.  Trust, integrated information technology and new product success , 2017 .

[47]  Richard J. Tersine,et al.  Customer‐aligned inventory strategies: agility maxims , 2000 .

[48]  Daniel J Flint,et al.  Compressing new product success-to-success cycle time , 2002 .

[49]  J. Arias,et al.  A relationship marketing approach to guanxi , 1998 .

[50]  Gavin K Reynolds,et al.  A big data approach to pharmaceutical flow properties , 2019, International journal of pharmaceutics.

[51]  Zhitao Guan,et al.  Achieving privacy-preserving big data aggregation with fault tolerance in smart grid , 2017 .

[52]  Raphaël Couturier,et al.  Comparison of Different Data Aggregation Techniques in Distributed Sensor Networks , 2017, IEEE Access.

[53]  Jorina Smeda,et al.  Distinctive organisational business imperatives of Big Data: a literature review , 2017, Electron. Libr..

[54]  Vijay Khatri,et al.  Managerial work in the realm of the digital universe: The role of the data triad , 2016 .

[55]  Santanu Mandal,et al.  An Empirical Investigation on E-retailer Agility, Customer Satisfaction, Commitment and Loyalty , 2017 .

[56]  Andrew K. Shenton.  Strategies for ensuring trustworthiness in qualitative research projects , 2004, Educ. Inf..

[57]  Casey G. Cegielski,et al.  Amassing and Analyzing Customer Data in the Age of Big Data: A Case Study of Haier’s Online-to-Offline (O2O) Business Model , 2015 .

[58]  E. Guba,et al.  Competing paradigms in qualitative research. , 1994 .

[59]  Z. Irani,et al.  Critical analysis of Big Data challenges and analytical methods , 2017 .

[60]  Clyde W. Holsapple,et al.  Supply chain agility: scale development , 2009 .

[61]  Lisa C . Troy,et al.  Cross-Functional Integration and New Product Success: An Empirical Investigation of the Findings , 2008 .

[62]  Pervaiz Akhtar,et al.  The Internet of Things, dynamic data and information processing capabilities, and operational agility , 2017, Technological Forecasting and Social Change.

[63]  T. Oliveira,et al.  Assessing business value of Big Data Analytics in European firms , 2017 .

[64]  Canon Tong,et al.  New product success: empirical evidence from SMEs in China , 2013 .

[65]  Ofir Turel,et al.  Increasing firm agility through the use of data analytics: The role of fit , 2017, Decis. Support Syst..

[66]  Gary L. Frankwick,et al.  Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective , 2016 .

[67]  V. Story,et al.  Complementary effect of entrepreneurial and market orientations on export new product success under differing levels of competitive intensity and financial capital , 2012 .

[68]  Varun Grover,et al.  Leveraging Information Technology Infrastructure to Facilitate a Firm's Customer Agility and Competitive Activity: An Empirical Investigation , 2012, J. Manag. Inf. Syst..

[69]  Manoj Kumar Tiwari,et al.  Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach , 2006, Eur. J. Oper. Res..

[70]  Na Wen,et al.  Contingent effects of managerial guanxi on new product development success , 2013 .

[71]  Yadong Luo,et al.  Guanxi and organizational dynamics: organizational networking in Chinese firms , 2001 .

[72]  Tracy Ann Sykes,et al.  Big data breaches and customer compensation strategies: Personality traits and social influence as antecedents of perceived compensation , 2017 .

[73]  Hsiu-Fang Hsieh,et al.  Three Approaches to Qualitative Content Analysis , 2005, Qualitative health research.

[74]  M. Wedel,et al.  Marketing Analytics for Data-Rich Environments , 2016 .

[75]  Sohvi Heaton,et al.  Dynamic Capabilities and Organizational Agility: Risk, Uncertainty and Entrepreneurial Management in the Innovation Economy , 2016 .

[76]  D. Polkinghorne.  Validity Issues in Narrative Research , 2007 .

[77]  Athanasios V. Vasilakos,et al.  Big data: From beginning to future , 2016, Int. J. Inf. Manag..

[78]  R. Chalmeta,et al.  Social customer relationship management: taking advantage of Web 2.0 and Big Data technologies , 2016, SpringerPlus.

[79]  Tom R. Burns,et al.  The Management of Innovation. , 1963 .

[80]  Junfeng Zhang,et al.  Leveraging Internal Resources and External Business Networks for New Product Success: A Dynamic Capabilities Perspective , 2017 .