Big data investments in knowledge and non-knowledge intensive firms: what the market tells us

2017 ◽  
Vol 21 (3) ◽  
pp. 623-639 ◽  
Author(s):  
Tingting Zhang ◽  
William Yu Chung Wang ◽  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Stock Market ◽  
Value Chain ◽  
Stock Prices ◽  
Economic Value ◽  
Information Value ◽  
Publicly Traded ◽  
Content Type ◽  
Knowledge Intensive

Purpose This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not. Design/methodology/approach This study is based on an event study using data from two stock markets in China. Findings The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along. Research limitations/implications This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets. Originality/value Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.

Analyzing Big Data through the lens of customer knowledge management

Kybernetes ◽  
2018 ◽  
Vol 47 (7) ◽  
pp. 1348-1362 ◽  
Author(s):  
Pasquale Del Vecchio ◽  
Giustina Secundo ◽  
Giuseppina Passiante
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Tourism Industry ◽  
Three Dimensions ◽  
Huge Amount ◽  
Customer Knowledge ◽  
Content Type ◽  
Customer Knowledge Management ◽  
Tourism Destinations ◽  
Knowledge Intensive

Purpose This paper aims to demonstrate how customer knowledge management (CKM) can opportunely support the process of value creation from Big Data. Focusing on tourism as a knowledge-intensive industry, the paper tries to contribute to the debate on management of Big Data by proposing CKM as a meaningful approach for transforming the huge amount of data available on social networks into valuable assets for competitiveness of tourism destinations. Design/methodology/approach The paper adopts a qualitative research methodology based on multiple exploratory case studies identified in a set of digital local events related to the Apulia destination (southern Italy). Findings Research findings demonstrate that the three dimensions of CKM (knowledge for, from and about customers) could be adopted as lens for analyzing the huge amount of data created for, from and about tourist experiences and for transforming them into valuable assets supporting the competitiveness of tourism destinations. Research limitations/implications Limitations are related to the industry and the regional dimension of the sample. Accordingly, more research is necessary to prove the validity of the approach and to assure its larger replicability. Practical implications Implications for the agenda of organizations and destinations’ makers for designing and implementing knowledge-based services and products arise. Originality/value Elements of originality reside into the adoption of CKM as framework to analyze Big Data in the tourism industry.

Big data analytics capabilities and knowledge management: impact on firm performance

2019 ◽  
Vol 57 (8) ◽  
pp. 1923-1936 ◽  
Author(s):  
Alberto Ferraris ◽  
Alberto Mazzoleni ◽  
Alain Devalle ◽  
Jerome Couturier
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Data Analytics ◽  
Structural Equation ◽  
Positive Impact ◽  
Big Data Analytics ◽  
Integrated Approach ◽  
Content Type ◽  
Decision Making Processes ◽  
External Sources

Purpose Big data analytics (BDA) guarantees that data may be analysed and categorised into useful information for businesses and transformed into big data related-knowledge and efficient decision-making processes, thereby improving performance. However, the management of the knowledge generated from the BDA as well as its integration and combination with firm knowledge have scarcely been investigated, despite an emergent need of a structured and integrated approach. The paper aims to discuss these issues. Design/methodology/approach Through an empirical analysis based on structural equation modelling with data collected from 88 Italian SMEs, the authors tested if BDA capabilities have a positive impact on firm performances, as well as the mediator effect of knowledge management (KM) on this relationship. Findings The findings of this paper show that firms that developed more BDA capabilities than others, both technological and managerial, increased their performances and that KM orientation plays a significant role in amplifying the effect of BDA capabilities. Originality/value BDA has the potential to change the way firms compete through better understanding, processing, and exploiting of huge amounts of data coming from different internal and external sources and processes. Some managerial and theoretical implications are proposed and discussed in light of the emergence of this new phenomenon.

Should knowledge management in organizations be rebranded?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maayan Nakash ◽  
Dan Bouhnik
Keyword(s):  
Knowledge Management ◽  
Organizational Context ◽  
Theory Approach ◽  
Content Type ◽  
Study Approach ◽  
Qualitative Research Methodology ◽  
Knowledge Intensive ◽  
Strategic Perspective ◽  
First Time

Purpose This study aims to examine the relevance of the term “knowledge management” (KM) in the organizational context, and deliberates whether there is a need for rebranding of this field. It also enriches the understanding regarding the appropriateness of the term “KM,” which was chosen to represent the discipline. Design/methodology/approach This study adopted a qualitative research methodology, and a case study approach was followed by conducting 19 semi-structured in-depth interviews with international KM experts working in a global consulting firm. The data were analyzed using a thematic analysis method based on the grounded theory approach. Findings The findings provide empirical evidence that attempts are being made to move away from the label “KM” in certain knowledge-intensive organizations. This study sheds light on the challenges associated with this term, which leads some to believe that the name of the discipline needs to change. Originality/value The present pioneering research contributes to empirical knowledge through investigation of an unexplored scientific field. To the best of the authors’ knowledge, for the first time, its uniqueness can be established by the fact that the opinions of KM professionals are being heard regarding the “KM” label, as well as the need for a rebranding of this discipline in the organizational context. From a practical and strategic perspective, this study suggests that the research community and practitioners pay attention to attempts to shift away from the existing title identified in organizational practice.

Knowledge management measures: an empirical investigation of Indian cement industry

2019 ◽  
Vol 26 (3) ◽  
pp. 734-752 ◽  
Author(s):  
Manish Dave ◽  
Kanhaiya Singh ◽  
Arya Kumar ◽  
Sachin Kumar
Keyword(s):  
Knowledge Management ◽  
Value Chain ◽  
Management Practices ◽  
Reliability And Validity ◽  
Cement Industry ◽  
Sales Managers ◽  
Management Tools ◽  
Content Type ◽  
Management Measures ◽  
E Mail

Purpose The purpose of this paper is to develop knowledge management constructs comprising of KM processes and KM practices through marketing and sales to derive competitive advantage (CA) in the cement industry. Design/methodology/approach A thorough and detailed analysis of the literature was carried out to develop the measures for KM practices, KM processes and their impact on CA. A total of 65 variables affecting competitiveness in the form of questionnaire were developed. The questionnaire was administered through e-mail to 962 territory sales managers (TSM) and equivalent employed in the marketing and sales function of the cement organizations in India. A total of 121 valid and complete responses were received, representing a response rate of 12.6 percent. The factor analysis was carried out on the data collected to establish reliability and validity of the measures. Findings A total of seven constructs pertaining to knowledge management practices and processes and competitiveness that comprises of 65 variables have been developed. The statistical results establish that the constructs and the variables considered in the study are reliable and valid. Research limitations/implications The sample of respondents for developing constructs consisted of TSM and equivalent employed in the marketing and sales function of cement companies in India. Research scope can be enhanced in the future study by including middle and senior level managers in cement companies to better diagnose and understand perception of KM initiatives across different levels in the cement industry. The work can also be extended to incorporate inbound logistics and procurement that directly contributes to the overall value chain to have a holistic perspective. Practical implications The measures developed in this study would be effective management tools for the implementation of knowledge management initiatives in the marketing and sales function to ascertain their level of implementation and impact on the competitiveness. Originality/value This study is probably the first of its kind in India to provide KM measures combined for practices and processes to understand the relationship with competitiveness in cement companies pertaining to marketing and sales function. It provides valuable insights as a strategic tool for investing in KM initiatives.

Personal knowledge management and enactment of personal knowledge infrastructures as shadow IT

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Hossein Jarrahi ◽  
Rebecca Reynolds ◽  
Ali Eshraghi
Keyword(s):  
Knowledge Management ◽  
Knowledge Workers ◽  
Organizational Level ◽  
Personal Knowledge ◽  
Content Type ◽  
Organizational Contexts ◽  
Personal Knowledge Management ◽  
Consulting Firms ◽  
Individual Knowledge ◽  
Knowledge Intensive

Purpose Personal knowledge management (KM) lends new emphasis to ways through which individual knowledge workers engage with knowledge in organizational contexts. This paper aims to go beyond an organizational approach to KM to examine key personal KM and knowledge building (KB) practices among adult professionals. Design/methodology/approach This paper presents a summary of the findings from interviews with 58 consultants from 17 managing consulting firms. Participants were selected based on their knowledge-intensive roles and their willingness to share information about their knowledge practices. Data analysis was inductive and revealed multiple personal KM activities common among research participants, and the way these are supported by informal ties and various technologies. Findings This work highlights ways in which “shadow information technology” undergirds personal knowledge infrastructures and supports KM and KB practices in the context of management consulting firms. The results uncover how personal knowledge infrastructures emerge from personal KM and KB practices, and the role of informal social networks as well as social media in supporting personal KM and KB. Research limitations/implications This study contributes an overall conceptual model of factors that help knowledge workers build a personal knowledge infrastructure. By affording an understanding of socially embedded personal KM activities, this work helps organizations create a balance between KM strategies at the organizational level and personal knowledge goals of individual workers. Originality/value Much of the previous research on KM adopts organizational approaches to KM, accentuating how organizations can effectively capture, organize and distribute organizational knowledge (primarily through KM systems).

scholarly journals Knowledge management activities in social enterprises: lessons for small and non-profit firms

2017 ◽  
Vol 21 (2) ◽  
pp. 376-396 ◽  
Author(s):  
Maria L. Granados ◽  
Souad Mohamed ◽  
Vlatka Hlupic
Keyword(s):  
Knowledge Management ◽  
Empirical Studies ◽  
Economic Value ◽  
Social Enterprises ◽  
Content Type ◽  
Non Profit ◽  
Starting Point ◽  
The Creation ◽  
Social Environmental ◽  
The Uk

Purpose This paper aims to explore what social enterprises (SEs) in the UK know and how they acquire, convert, apply and protect this knowledge. This will enable them to manage their knowledge effectively and, hence, improve their practices and maximise the creation of social, environmental and economic value. Design/methodology/approach This study follows a qualitative approach, comprising 21 interviews with founders and senior members of SEs in the UK. Findings The results show that the investigated SEs have knowledge management (KM) practices similar to the already identified in SMEs, associated with informality, reliance on external sources and focus on socialisation activities, but they have unique challenges on managing their knowledge related to their hybrid mission, to include social and economic objectives and their closed relationship with stakeholders. Research limitations/implications As there is limited research on KM practices in SEs; they were defined based on previous studies in large, private and public companies. Therefore, not all practices may be included. This research is a starting point in the study of KM in SEs. Practical implications This study identifies knowledge activities that enable the creation of social, environmental and economic value in SEs. This allows SEs, small firms and non-profit organisations to review their current practices and develop plans for their further improvement. Originality/value This paper is one of the first empirical studies exploring KM practices in SEs, highlighting their informal nature as well as their impact in and on the enterprise.

Competitive intelligence as a coping strategy for academic libraries in South Africa

2020 ◽  
Vol 41 (6/7) ◽  
pp. 593-606
Author(s):  
Smangele P. Moyane ◽  
Luyanda Dube ◽  
Ntando Nkomo ◽  
Patrick Ngulube
Keyword(s):  
South Africa ◽  
Value Chain ◽  
Academic Libraries ◽  
Design Methodology ◽  
Response Rate ◽  
Information Value ◽  
Competitive Intelligence ◽  
Library Directors ◽  
Content Type ◽  
User Expectations

PurposeThis study examined the extent to which public academic libraries in South Africa coped with the changing information environment by using competitive intelligence (CI) to attain competitiveness.Design/methodology/approachThe study adopted positivism as the main philosophical lens and also incorporated qualitative elements to augment the quantitative data through a survey research design. Questionnaires were e-mailed to 25 directors of public academic libraries in South Africa and 17 were returned, yielding a 68% response rate. Attempts were made to reach to the 25 directors through semi-structured telephonic interviews, and only eight responded some through their representatives, yielding a 32% response rate. Using two instruments permitted the triangulation of data. A noted limitation of the study is that some library directors neither responded to the questionnaire nor the interview.FindingsFindings revealed that various competitive intelligence techniques were employed; however, their implementation was not formalised. Competitiveness was driven by various factors such as rivalries in the information value chain; relevance; financial and budgetary constraints; changing user expectations and evolving technology.Originality/valueThis study is novel because there is a dearth of literature on implementation and use of competitive intelligence in academic libraries in South Africa.

How the Internet of Things can help knowledge management: a case study from the automotive domain

2017 ◽  
Vol 21 (1) ◽  
pp. 57-70 ◽  
Author(s):  
Lorna Uden ◽  
Wu He
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Internet Of Things ◽  
Current Knowledge ◽  
Time Data ◽  
Content Type ◽  
Useful Knowledge ◽  
Iot Devices ◽  
The Internet Of Things

Purpose Current knowledge management (KM) systems cannot be used effectively for decision-making because of the lack of real-time data. This study aims to discuss how KM can benefit by embedding Internet of Things (IoT). Design/methodology/approach The paper discusses how IoT can help KM to capture data and convert data into knowledge to improve the parking service in transportation using a case study. Findings This case study related to intelligent parking service supported by IoT devices of vehicles shows that KM can play a role in turning the incoming big data collected from IoT devices into useful knowledge more quickly and effectively. Originality/value The literature review shows that there are few papers discussing how KM can benefit by embedding IoT and processing incoming big data collected from IoT devices. The case study developed in this study provides evidence to explain how IoT can help KM to capture big data and convert big data into knowledge to improve the parking service in transportation.

Asymmetric impact of exchange rate changes on stock returns: evidence of two de facto regimes

2019 ◽  
Vol 19 (2) ◽  
pp. 147-173
Author(s):  
Walid M.A. Ahmed
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Spillover Effects ◽  
Content Type ◽  
Currency Depreciation ◽  
Long Run ◽  
Exchange Rate Changes

Purpose This study focuses on Egypt’s recent experience with exchange rate policies, examining the existence of spillover effects of exchange rate variations on stock prices across two different de facto regimes and whether these effects, if any, are asymmetric. Design/methodology/approach The empirical analysis is carried out using a nonlinear autoregressive distributed lag modeling framework, which permits testing for the presence of short- and long-run asymmetries. Relevant local and global factors are also included in the analysis as control variables. The authors divide the entire sample into a soft peg period and a free float one. Findings Over the soft peg regime period, both positive and negative changes in EGP/USD exchange rates seem to have a significant impact on stock returns, whether in the short or long run. Short-term asymmetric effects vanish in the free float period, while long-term asymmetries continue to exist. By and large, the authors find that currency depreciation tends to exercise a stronger influence on stock returns than does currency appreciation. Practical implications The results offer important insights for investors, regulators and policymakers. With the domestic currency depreciation having a negative impact on stock prices, investors should contemplate implementing appropriate currency hedging strategies to abate depreciation risks and, hence, preserve their expected rate of return on the Egyptian pound-denominated investments. In the current post-flotation era, the government could pursue a flexible inflation targeting monetary policy framework, with a view to both lowering the soaring inflation toward an announced target rate and stabilizing economic growth. The Central Bank of Egypt (CBE) could adopt indirect monetary policy instruments to secure tightened liquidity conditions. Besides, the CBE could raise policy rates to incentivize people to keep their money in local currency-denominated instruments, instead of dollarizing their savings, thereby relieving banks of foreign currency demand pressures. Nevertheless, while being beneficial to the country’s real economy on several aspects, such contractionary monetary measures may temporarily impinge on stock market performance. Accordingly, policymakers should consider precautionary measures that reduce the potential for price distortions and unnecessary volatility in the stock market. Originality/value To the best of the authors’ knowledge, the current study represents the first attempt to explore the potential impact of exchange rate changes under different regimes on Egypt’s stock market, thus contributing to the relevant research in this area.

Stock prices' long memory in China and the United States

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhengxun Tan ◽  
Yao Fu ◽  
Hong Cheng ◽  
Juan Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Long Memory ◽  
Stock Markets ◽  
Information Disclosure ◽  
Structural Breaks ◽  
Efficient Market Hypothesis ◽  
The United States ◽  
Chinese Stock Market ◽  
Content Type

PurposeThis study aims to examine the long memory as well as the effect of structural breaks in the US and the Chinese stock markets. More importantly, it further explores possible causes of the differences in long memory between these two stock markets.Design/methodology/approachThe authors employ various methods to estimate the memory parameters, including the modified R/S, averaged periodogram, Lagrange multiplier, local Whittle and exact local Whittle estimations.FindingsChina's two stock markets exhibit long memory, whereas the two US markets do not. Furthermore, long memory is robust in Chinese markets even when we test break-adjusted data. The Chinese stock market does not meet the efficient market hypothesis (EMHs), including the efficiency of information disclosure, regulations and supervision, investors' behavior, and trading mechanisms. Therefore, its stock prices' sluggish response to information leads to momentum effects and long memory.Originality/valueThe authors elaborately illustrate how long memory develops by analyzing not only stock market indices but also typical individual stocks in both the emerging China and the developed US, which diversifies the EMH with wider international stylized facts and findings when compared with previous literature. A couple of tests conducted to analyze structural break effects and spurious long memory demonstrate the reliability of the results. The authors’ findings have significant implications for investors and policymakers worldwide.

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