Integrating the Split/Analyze/Meta-Analyze (SAM) Approach and a Multilevel Framework to Advance Big Data Research in Psychology

2018 ◽  
Vol 226 (4) ◽  
pp. 274-283 ◽  
Author(s):  
Yucheng Eason Zhang ◽  
Siqi Liu ◽  
Shan Xu ◽  
Miles M. Yang ◽  
Jian Zhang
Keyword(s):  
Big Data ◽  
Computer Science ◽  
Analytical Techniques ◽  
Future Research ◽  
Firm Level ◽  
Research Directions ◽  
Research Issues ◽  
Country Level ◽  
Multilevel Research ◽  
Future Research Directions

Abstract. Though big data research has undergone dramatic developments in recent decades, it has mainly been applied in disciplines such as computer science and business. Psychology research that applies big data to examine research issues in psychology is largely lacking. One of the major challenges regarding the use of big data in psychology is that many researchers in the field may not have sufficient knowledge of big data analytical techniques that are rooted in computer science. This paper integrates the split/analyze/meta-analyze (SAM) approach and a multilevel framework to illustrate how to use the SAM approach to address multilevel research questions with big data. Specifically, we first introduce the SAM approach and then illustrate how to implement this to integrate two big datasets at the firm level and country level. Finally, we discuss theoretical and practical implications, proposing future research directions for psychology scholars.

Team-Level Constructs

2019 ◽  
Vol 6 (1) ◽  
pp. 325-348
Author(s):  
David Chan
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Future Research ◽  
Methodological Issues ◽  
Research Directions ◽  
Substantive Content ◽  
Multilevel Research ◽  
Future Research Directions ◽  
Changes Over Time ◽  
Over Time

Studies of team-level constructs can produce new insights when researchers explicitly take into account several critical conceptual and methodological issues. This article explicates the conceptual bases for multilevel research on team constructs and discusses specific issues relating to conceptual frameworks, measurement, and data analysis. To advance programmatic research involving team-level constructs, several future research directions concerning issues of substantive content (i.e., changes in the nature of work and teams, member-team fit, linking team-level constructs to higher-level constructs) and strategic approaches (i.e., the construct's theoretical roles, dimensionality and specificity, malleability and changes over time, relationships with Big Data) are proposed.

Coexisting Agency and Stewardship Governance in Family Firms: An Empirical Investigation of Individual-Level and Firm-Level Effects

2017 ◽  
Vol 30 (4) ◽  
pp. 347-368 ◽  
Author(s):  
Kristen Madison ◽  
Franz W. Kellermanns ◽  
Timothy P. Munyon
Keyword(s):  
Family Firms ◽  
Empirical Investigation ◽  
Future Research ◽  
Firm Level ◽  
Research Directions ◽  
Agent Behavior ◽  
Individual Level ◽  
Future Research Directions ◽  
Level Performance ◽  
Triadic Data

This article theoretically and empirically intertwines agency and stewardship theories to examine their distinct and combined influences on family firms. Primary matched triadic data from CEOs, family employees, and nonfamily employees in 77 family firms suggest that agency and stewardship governance affects individual-level behavior and firm-level performance. Specifically, agent behavior is highest under conditions of coexisting low agency governance and high stewardship governance and is lowest when agency and stewardship governance coexist at high levels. Furthermore, when high levels of agency and stewardship governance coexist, family firm performance is the highest. Theoretical implications and future research directions are discussed.

Future Research Directions in E-Tourism Studies

Big Data ◽  
2016 ◽  
pp. 2368-2387
Author(s):  
Hajime Eto
Keyword(s):  
Big Data ◽  
Future Research ◽  
Research Directions ◽  
Scientific Methods ◽  
Tourism Studies ◽  
The Future ◽  
Future Research Directions ◽  
And Behaviors ◽  
Public Voice

As this book has the limited numbers of chapters and pages, many important issues remain unanalyzed. This chapter picks up and roughly discusses some of them for the future analyses in more analytical ways. The focuses are placed on how to apply the data scientific methods to the analyses of public voice, claims and behaviors of tourists, customers and the general publics by using the big data already acquired and stored somewhere.

Big Data Analytics Driven Supply Chain Transformation

2019 ◽  
pp. 106-124 ◽  
Author(s):  
Mondher Feki
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Research Directions ◽  
Digital Platforms ◽  
New Frontier ◽  
Future Research Directions ◽  
Chain Transformation

Big data has emerged as the new frontier in supply chain management; however, few firms know how to embrace big data and capitalize on its value. The non-stop production of massive amounts of data on various digital platforms has prompted academics and practitioners to focus on the data economy. Companies must rethink how to harness big data and take full advantage of its possibilities. Big data analytics can help them in giving valuable insights. This chapter provides an overview of big data analytics use in the supply chain field and underlines its potential role in the supply chain transformation. The results show that big data analytics techniques can be categorized into three types: descriptive, predictive, and prescriptive. These techniques influence supply chain processes and create business value. This study sets out future research directions.

Augmented Reality Research for Architecture and Design

2012 ◽  
pp. 225-237 ◽  
Author(s):  
Mi Jeong Kim ◽  
Xiangyu Wang ◽  
Xingquan Zhu ◽  
Shih-Chung Kang
Keyword(s):  
Augmented Reality ◽  
Emerging Technology ◽  
Future Research ◽  
Research Directions ◽  
Research Issues ◽  
The Past ◽  
Growing Body ◽  
Future Research Directions ◽  
Architecture And Design

A growing body of research has shown that Augmented Reality (AR) has the potential to contribute to interaction and visualization for architecture and design. While this emerging technology has only been developed for the past decade, numerous journals and conferences in architecture and design have published articles related to AR. This chapter reviews 44 articles on AR especially related to the architecture and design area that were published from 2005 to 2011. Further, this chapter discusses the representative AR research works in terms of four aspects: AR concept, AR implementation, AR evaluation, and AR industry adoption. The chapter draws conclusions about major findings, research issues, and future research directions through the review results. This chapter will be a basis for future research of AR in architecture and design areas.

Unit of Analysis in Digitally-Enabled Electronic Procurement Research

2020 ◽  
pp. 83-103
Author(s):  
Md Mahbubur Rahim ◽  
Maryam Jabberzadeh ◽  
Nergiz Ilhan
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Critical Issue ◽  
Future Research ◽  
Research Directions ◽  
Research Issues ◽  
Unit Of Analysis ◽  
Electronic Procurement ◽  
Future Research Directions ◽  
Methodological Concern

E-procurement systems that have been in place for over a decade have begun incorporating digital tools like big data, cloud computing, internet of things, and data mining. Hence, there exists a rich literature on earlier e-procurement systems and advanced digitally-enabled e-procurement systems. Existing literature on these systems addresses many research issues (e.g., adoption) associated with e-procurement. However, one critical issue that has so far received no rigorous attention is about “unit of analysis,” a methodological concern of importance, for e-procurement research context. Hence, the aim of this chapter is twofold: 1) to discuss how the notion of “unit of analysis” has been conceptualised in the e-procurement literature and 2) to discuss how its use has been justified by e-procurement scholars to address the research issues under investigation. Finally, the chapter provides several interesting findings and outlines future research directions.

Computational and Data Mining Perspectives on HIV/AIDS in Big Data Era

2022 ◽  
pp. 1477-1503
Author(s):  
Ali Al Mazari
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Sector ◽  
Future Research ◽  
Research Directions ◽  
Scientific Disciplines ◽  
Future Research Directions ◽  
Hiv Aids

HIV/AIDS big data analytics evolved as a potential initiative enabling the connection between three major scientific disciplines: (1) the HIV biology emergence and evolution; (2) the clinical and medical complex problems and practices associated with the infections and diseases; and (3) the computational methods for the mining of HIV/AIDS biological, medical, and clinical big data. This chapter provides a review on the computational and data mining perspectives on HIV/AIDS in big data era. The chapter focuses on the research opportunities in this domain, identifies the challenges facing the development of big data analytics in HIV/AIDS domain, and then highlights the future research directions of big data in the healthcare sector.

On the Road to Ephesus

2015 ◽  
pp. 102-125
Author(s):  
Suzanne Roff-Wexler
Keyword(s):  
Big Data ◽  
Future Research ◽  
Review Of Literature ◽  
Healthcare Organizations ◽  
Research Directions ◽  
The Road ◽  
Future Research Directions ◽  
On The Road ◽  
Definition Of

Following a brief review of literature on big data as well as wisdom, this chapter provides a definition of data-based wisdom in the context of healthcare organizations and their visions. The author addresses barriers and ways to overcome barriers to data-based wisdom. Insights from interviews with leading healthcare professionals add practical meaning to the discussion. Finally, future research directions and questions are suggested, including the role of synchronicity and serendipity in data-based wisdom. In this chapter, developing data-based wisdom systems that flourish Wisdom, Virtue, Intellect, and Knowledge are encouraged.

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