scholarly journals Value Chain Creation in Business Analytics

2021 ◽  
Vol 29 (4) ◽  
pp. 131-147
Author(s):  
Dong Yoo ◽  
James J. Roh
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Information Value ◽  
Organizational Resilience ◽  
Business Analytics ◽  
Quality Outcomes ◽  
A Value ◽  
Net Benefits ◽  
Analytical Technology ◽  
Practical Implications

Firms are awash in big data and analytical technology as part of the process of deriving values in the current turbulent environment. The literature has reached a consensus that investments in technology only may not reap benefits from business analytics (BA). As such, the main purpose of BA is not about how to install technical capabilities, but about how to create a process whereby a firm builds a value chain converting data into insights and ultimately into quality outcomes. Drawing upon the theory of the information value chain, this study develops a BA value chain creation model and tests it with 268 firms. Results show that organizational resilience, absorptive capacity, and analytical IT capabilities are critical antecedents of analytical decision-making quality, which in turn influences BA net benefits. In particular, organizational resilience emerges as a more significant determinant of analytical decision-making quality than technology and people in the BA value chain creation. Theoretical and practical implications are also discussed in this paper.

Increasing the viability of project selection and prioritization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
Project Work ◽  
Business Analytics ◽  
Operating Environment ◽  
Content Type ◽  
Pertinent Information ◽  
Practical Implications

Purpose This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Design/methodology/approach This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Findings Business analytics (BA) can help firms better select and prioritize project work they undertake. Data generated through analytics permits awareness of changes in the operating environment and can be used to inform sensemaking and alongside intuition to enhance decision-making. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The upside of collective board values in decision-making

2018 ◽  
Vol 34 (7) ◽  
pp. 20-22
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Reading Time ◽  
Strategic Decisions ◽  
Content Type ◽  
A Value ◽  
Challenges And Opportunities ◽  
Financial Interests ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This research paper concentrates on how boards can agree collective values that guide their strategic decisions, in a way that balances financial interests with the wellbeing and development of their people. Having a value-led strategy underpinning each response to challenges and opportunities creates welcome transparency in an organization. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Why Apple’s product magic continues to amaze – skills of the world’s #1 value chain integrator

2014 ◽  
Vol 42 (6) ◽  
pp. 17-28 ◽  
Author(s):  
Will Mitchell
Keyword(s):  
Value Chain ◽  
Customer Value ◽  
Management Practices ◽  
Social Contexts ◽  
Corporate Value ◽  
Content Type ◽  
Corporate Leaders ◽  
A Value ◽  
Practical Implications ◽  
The Way

Purpose – Apple’s amazing run of blockbusters – iPhone, iPad, iPod, iTunes, multiple iterations of the Mac computer, and going all the way back to the Apple II – has created a fan base of consumers willing to pay premium prices and produced enormous corporate value. This case aims to look at the strategies, value chain integration skills and management practices that underlie Apple’s ability to bring its designs to commercial stardom and propel shareholder value. Design/methodology/approach – The case examines two related skills that the company has developed since the late 1990s that are critical complements to Apple’s design talents: its ability to combine “build, borrow and buy” strategies and its world-leading abilities as a value chain integrator. Findings – Apple has uniquely sophisticated “build, borrow and buy” (BBB) expertise throughout its management, going all the way up to its CEO Tim Cook. The company’s lengthy success record proves it knows when and how to develop products and components internally, when to ally with other firms and when and how to acquire and integrate other companies. Research limitations/implications – This case is based on publically available sources. Practical implications – Despite working with such a large and powerful set of vendors and partners, Apple harvests much of the value in the relationships. Originality/value – The case shows how corporate leaders and personnel throughout the company maintain a systematic view of customer value, the value chain that delivers that value and the competitive and social contexts that shape value demands, so that they can communicate and coordinate activities of multiple vendors throughout the ecosystem rather than simply manage a series of one-to-one relationships.

Business Analytics Capabilities and Use: A Value Chain Perspective

2017 ◽  
pp. 41-54 ◽  
Author(s):  
Torupallab Ghoshal ◽  
Rudolph T. Bedeley ◽  
Lakshmi S. Iyer ◽  
Joyendu Bhadury
Keyword(s):  
Value Chain ◽  
Business Analytics ◽  
A Value

scholarly journals The Viability of Outsourcing in Organisational Performance: Benefits and Risks

2021 ◽  
Author(s):  
Mário Franco ◽  
Margarida Rodrigues ◽  
Rui Silva
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Transaction Costs ◽  
Value Chain ◽  
Organisational Performance ◽  
Use Of Resources ◽  
A Value ◽  
Organisational Structures ◽  
Decision Making Model

Outsourcing is part of a system, as it includes products and services integrated in a value chain and which are performed by an external (contracted) firm, aiming to establish an interdependent, collaborative and trusting relationship between the contracting and contracted firms. Like any dimension of business in organisations, changes in organisational structures and in how the service is produced/provided, outsourcing brings benefits and risks. Therefore, from literature review method, this chapter aims to explore the concept of outsourcing as a differentiating tool in organisations’ performance, emphasising the benefits and risks. The results showed the dimensions to consider in the decision to implement outsourcing, which are: (1) transaction costs, (2) use of resources, and (3) collaboration between the parties. The contribution of the study is to present a synopsis of the outsourcing topic, specifically the theories that support it, its benefits and risks. Additionally, a decision-making model is presented, in the certainty of its usefulness for the organizations’ managers.

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.

scholarly journals Bayesian maintenance decision optimisation based on computing the information value from condition inspections

2021 ◽  
pp. 1748006X2097812
Author(s):  
Guang Zou ◽  
Kian Banisoleiman ◽  
Arturo González
Keyword(s):  
Decision Making ◽  
Structural Integrity ◽  
Fatigue Cracking ◽  
Cost Effective ◽  
Offshore Structures ◽  
Information Value ◽  
Bayesian Decision ◽  
Maintenance Strategies ◽  
Optimal Maintenance ◽  
Maintenance Decision

A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.

scholarly journals Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19

2021 ◽  
Vol 13 ◽  
pp. 184797902110233
Author(s):  
Stefania Bait ◽  
Serena Marino Lauria ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Multinational Enterprises ◽  
Value Added ◽  
Plant Performance ◽  
Multi Criteria Decision Making ◽  
African Countries ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Decision Making Model

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts.

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