A Big Data and FMEA-based construction quality risk evaluation model considering project schedule for Shanghai apartment projects

2019 ◽  
Vol 37 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Guofeng Ma ◽  
Ming Wu
Keyword(s):  
Big Data ◽  
Project Managers ◽  
Project Schedule ◽  
Construction Quality ◽  
Content Type ◽  
Project Quality ◽  
Model Based ◽  
Multiple Variables ◽  
Quality Risk ◽  
The Relationship

Purpose The purpose of this paper is to mine information on the construction process of previous projects to develop a construction plan that meets both quality requirements and schedule constraints. Design/methodology/approach This paper uses a failure mode and effect analysis to evaluate the construction quality of 311 apartments in Shanghai. The authors also evaluate construction-scheduling control using the earned value management technique and implement an artificial neural network to correlate the results. The authors then develop a quality risk and schedule correlation model based on Big Data. The model can predict the relationship between the planned schedule and the project quality risk using multiple variables such as the number of layers, the schedule performance index and budget costs. Findings The methodology offers an innovative approach for assessment on the relationship between quality risk and project schedule. The authors have also built a multiple regression analysis model for comparative purposes with the model. The results show that the proposed model can better describe the relationship. The model can provide a quantitative quality risk value that changes with the planned schedule, as well as help project managers to understand the relationship between quality risk and project scheduling more accurately. Research limitations/implications The research approach only focuses on quality risk under the impact of scheduling. Future efforts might focus on developing a model that connects failure models with project schedules and costs in order to improve the effort of quality management. Practical implications The model based on Big Data in this paper is developed using real projects and reflects the relationship between project quality risk and scheduling in real environments. The created application provides support for project managers to develop and adjust quality plans and schedules, thereby reducing deviations in quality and scheduling objectives. Originality/value The authors make full use of historical project data from the perspective of both quality and schedule management, and provide a novel method to intelligently and objectively analyze the relationship between quality risk and scheduling.

scholarly journals Big data, technology capability and construction project quality: a cross-level investigation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Linhua Sang ◽  
Mingchuan Yu ◽  
Han Lin ◽  
Zixin Zhang ◽  
Ruoyu Jin
Keyword(s):  
Big Data ◽  
Quality Improvement ◽  
Project Management ◽  
Construction Project ◽  
Short Time Interval ◽  
Quality Performance ◽  
Content Type ◽  
Project Quality ◽  
Technology Capability ◽  
The Relationship

PurposeEmbracing big data has been at the forefront of research for project management. Although there is a consensus that the adoption of big data has significantly positive impact on project performance, far less is known about how this innovative information technology becomes an effective driver of construction project quality improvement. This study aims to better understand the mechanism and conditions under which big data can effectively improve project quality performance.Design/methodology/approachAdopting Chinese construction enterprises as samples, the theoretical framework proposed in this paper is verified by the empirical results of the two-level hierarchical linear model. The moderated mediation analysis is also conducted to test the hypotheses. Finally, the empirical findings are validated by a comparative case study.FindingsThe results show that big data facilitates the development of technology capability, which further produces remarkable quality performance. That is, a project team's technology capability acts as a mediator in the relationship between organizational adaptability of big data and predictive analytics and project quality performance. It is also observed that two types of project team interdependence (goal and task interdependence) positively moderate the mediation effect.Research limitations/implicationsThe questionnaire study from China only represents the relationship within a short time interval in the current context. Future studies should apply longitudinal designs to properly test the causality and use multiple data sources to ensure the validity and robustness of the conclusions.Practical implicationsThe value of big data in terms of quality improvement could not be determined in a vacuum; it also depends on the internal capability development and elaborate design of project governance.Originality/valueThis study provides an extension of the existing big data studies and fuels the ongoing debate on its actual outcomes in project management. It not only clarifies the direct effect of big data on project quality improvement but also identifies the mechanism and conditions under which the adoption of big data can play an effective role.

Dave Snowden on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 12-17 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Theory And Practice ◽  
Content Type ◽  
Face To Face ◽  
The Relationship ◽  
A Company ◽  
Practical Implications ◽  
Scientific Officer

Purpose Dave Snowden has been an important voice in knowledge management over the years. As the founder and chief scientific officer of Cognitive Edge, a company focused on the development of the theory and practice of social complexity, he offers informative views on the relationship between big data/analytics and KM. Design/methodology/approach A face-to-face interview was held with Dave Snowden in May 2015 in Auckland, New Zealand. Findings According to Snowden, analytics in the form of algorithms are imperfect and can only to a small extent capture the reasoning and analytical capabilities of people. For this reason, while big data/analytics can be useful, they are limited and must be used in conjunction with human knowledge and reasoning. Practical implications Snowden offers his views on big data/analytics and how they can be used effectively in real world situations in combination with human reasoning and input, for example in fields from resource management to individual health care. Originality/value Snowden is an innovative thinker. He combines knowledge and experience from many fields and offers original views and understanding of big data/analytics, knowledge and management.

Big data analytics capabilities and organizational performance: the mediating effect of dual innovations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Su ◽  
Weipeng Zeng ◽  
Manhua Zheng ◽  
Xiaoli Jiang ◽  
Wenhe Lin ◽  
...  
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Empirical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Mediating Effect ◽  
Content Type ◽  
Mediating Role ◽  
The Relationship

PurposeFollowing the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.Design/methodology/approachDrawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.FindingsThe results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.Originality/valueThe conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

Multisensory experience for enhancing hotel guest experience

2019 ◽  
Vol 31 (11) ◽  
pp. 4313-4337 ◽  
Author(s):  
Minwoo Lee ◽  
Seonjeong (Ally) Lee ◽  
Yoon Koh
Keyword(s):  
Big Data ◽  
Customer Satisfaction ◽  
Business Intelligence ◽  
Critical Role ◽  
Big Data Analytics ◽  
Cognitive Effort ◽  
Content Type ◽  
The Relationship ◽  
Multisensory Experience

Purpose This study aims to investigate the effect of customers’ multisensory service experience on customer satisfaction with cognitive effort and affective evaluations using big data and business intelligence techniques. Design/methodology/approach Online customer reviews for all New York City hotels were collected from Tripadvisor.com and analyzed through business intelligence and big data analytics techniques including data mining, text analytics, sentiment analysis and regression analysis. Findings The current study identifies the relationship between affective evaluations (i.e. positive affect and negative affect) and customer satisfaction. Research findings also find the negative effect of reviewer’s cognitive effort on satisfaction rating. More importantly, this study demonstrates the moderating role of multisensory experience as an innovative marketing tool on the relationship between affect/cognitive evaluation and customer satisfaction in the hospitality setting. Originality/value This study is the first study to explore the critical role of sensory marketing on hotel guest experience in the context of hotel customer experience and service innovation, based on big data and business intelligence techniques.

Linking transformational leadership and “multi-dimensions” of project success

2019 ◽  
Vol 13 (1) ◽  
pp. 103-127 ◽  
Author(s):  
Umer Zaman ◽  
Shahid Nawaz ◽  
Sidra Tariq ◽  
Asad Afzal Humayoun
Keyword(s):  
Transformational Leadership ◽  
Structural Equation ◽  
Structural Model ◽  
Project Success ◽  
Higher Order ◽  
Project Managers ◽  
Second Order ◽  
Equation Modeling ◽  
Content Type ◽  
The Relationship

Purpose Transformational leadership, flexibility and visibility improves project responsiveness to highly unpredictable and impactful events referred as the ‘black swans’ in mega projects (Bloch et al., 2012; Raziq et al., 2018; Zailani et al., 2016). However, these concepts have never been empirically tested in a single framework to determine their significant impact on multi-dimensional project success. The purpose of this paper is to investigate the interactional effects of project flexibility and project visibility on the relationship between transformational leadership and “multi-dimensions” of project success including meeting design goals; impact on customers and benefits to project-based organization. Design/methodology/approach Empirical data derived from cross-sectional survey of 160 project managers from telecom intensive companies in Pakistan were used to test the conceptual framework developed from recent literature. Partial least squares-structural equation modeling (PLS-SEM) provided detailed analysis of the measurement and structural model. The most recent reflective–formative PLS-SEM approach for higher-order constructs has been introduced. Findings The results indicate that project managers’ transformational leadership (β = 0.348, p < 0.01), project flexibility (β = 0.221, p < 0.01) and project visibility (β = 0.366, p < 0.01) are positively related with the multi-dimensional project success (second-order formative) construct. Interestingly, the relationship between transformational leadership and project success is influenced by significantly negative moderations established through project flexibility (β = −0.100, p < 0.01) and project visibility (β = −0.093, p < 0.05). Research limitations/implications This study in the telecom sector examined the interactional effects of risk mitigating strategies (i.e. project flexibility and project visibility) on the relationship between transformational leadership and multi-dimensional project success. This study creates a basis for future investigations extending to various project types and relevant to different industries especially those involving higher-order (formative) assessments of project success. Practical implications The study findings assist project leaders to meet their escalating commitments in achieving project success from a multi-dimensional standpoint. Additionally, this study underscores a renewed perspective of transformational leadership and project outcomes. Despite prevailing understanding developed through prior research, transformational leadership may become less favorable for project success in conditions of increased flexibility and visibility in projects. Originality/value Earlier studies have overlooked the multi-dimensional nature of project success (second-order formative) construct, despite several attempts to examine the interplay between transformational leadership and project success. Based on the knowledge gap and non-existence of empirical evidence, the authors introduced and empirically tested the moderating role of project flexibility and project visibility in the relationship between transformational leadership and multi-dimensional project success.

Value that matters: intellectual capital and big data to assess performance in healthcare. An empirical analysis on the European context

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ginevra Gravili ◽  
Francesco Manta ◽  
Concetta Lucia Cristofaro ◽  
Rocco Reina ◽  
Pierluigi Toma
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Healthcare System ◽  
Healthcare Sector ◽  
Healthcare Organizations ◽  
Content Type ◽  
Structural Capital ◽  
And Performance ◽  
The Relationship

PurposeThe aim of this paper is to analyze and measure the effects of intellectual capital (IC), i.e. human capital (HC), relational capital (RC) and structural capital (SC), on healthcare industry organizational performance and understanding the role of data analytics and big data (BD) in healthcare value creation (Wang et al., 2018). Through the assessment of determined variables specific for each component of IC, the paper identifies the guidelines and suggests propositions for a more efficient response in terms of services provided to citizens and, specifically, patients, as well as predicting effective strategies to improve the care management efficiency in terms of cost reduction.Design/methodology/approachThe study has a twofold approach: in the first part, the authors operated a systematic review of the academic literature aiming to enquire the relationship between IC, big data analytics (BDA) and healthcare system, which were also the descriptors employed. In the second part, the authors built an econometric model analyzed through panel data analysis, studying the relationship between IC, namely human, relational and structural capital indicators, and the performance of healthcare system in terms of performance. The study has been conducted on a sample of 28 European countries, notwithstanding the belonging to specific international or supranational bodies, between 2011 and 2016.FindingsThe paper proposes a data-driven model that presents new approach to IC assessment, extendable to other economic sectors beyond healthcare. It shows the existence of a positive impact (turning into a mathematical inverse relationship) of the human, relational and structural capital on the performance indicator, while the physical assets (i.e. the available beds in hospitals on total population) positively mediates the relationship, turning into a negative impact of non-IC related inputs on healthcare performance. The result is relevant in terms of managerial implications, enhancing the opportunity to highlight the crucial role of IC in the healthcare sector.Research limitations/implicationsThe relationship between IC indicators and performance could be employed in other sectors, disseminating new approaches in academic research. Through the establishment of a relationship between IC factors and performance, the authors implemented an approach in which healthcare organizations are active participants in their economic and social value creation. This challenges the views of knowledge sharing deeply held inside organizations by creating “new value” developed through a more collaborative and permeated approach in terms of knowledge spillovers. A limitation is given by a fragmented policymaking process which carries out different results in each country.Practical implicationsThe analysis provides interesting implications on multiple perspectives. The novelty of the study provides interesting implications for managers, practitioners and governmental bodies. A more efficient healthcare system could provide better results in terms of cost minimization and reduction of hospitalization period. Moreover, dissemination of new scientific knowledge and drivers of specialization enhances best practices sharing in the healthcare sector. On the other hand, an improvement in preventive medicine practices could help in reducing the overload of demand for curative treatments, on the perspective of sharply decreasing the avoidable deaths rate and improving societal standards.Originality/valueThe authors provide a new holistic framework on the relationship between IC, BDA and organizational performance in healthcare organizations through a systematic review approach and an empirical panel analysis at a multinational level, which is quite a novelty regarding the healthcare. There is little research focussed on healthcare industries' organizational performance, and, specifically, most of the research on IC in healthcare delivered results in terms of theoretical contribution and qualitative analyzes. The authors even contributed to analyze the healthcare industry in the light of the possible existence of synergies and networks among countries.

Talent management under a big data induced revolution

2019 ◽  
Vol 57 (8) ◽  
pp. 2010-2031 ◽  
Author(s):  
Kaidi Zhang ◽  
Xiao Jia ◽  
Jin Chen
Keyword(s):  
Big Data ◽  
Servant Leadership ◽  
Boundary Conditions ◽  
Negative Relationship ◽  
Talent Management ◽  
Mediating Effect ◽  
Hierarchical Regression ◽  
Content Type ◽  
Negative Effect ◽  
The Relationship

PurposeThe emerging natures of big data – volume, velocity, variety, value and veracity – exert higher stress on employees and demand greater creativity from them, causing extreme difficulties in the talent management of organizations in the big data era. The purpose of this paper is to explore the effect of challenge stressors on creativity and the boundary conditions of the relationship.Design/methodology/approachMultisource data were collected including 593 followers and their 98 supervisors from organizations that are confronting a big data induced management revolution. Hierarchical regression analysis and bootstrapping analysis were used to test the mediation and moderation mechanism.FindingsThe results showed that job burnout mediated the negative relationship between challenge stressors and creativity and that this indirect effect was attenuated by an employee’s core self-evaluation (CSE) and servant leadership. In contrast, whether work engagement mediated the relationship between challenge stressors and creativity was contingent on the level of an employee’s CSE and servant leadership. Specifically, the mediating effect was significant only when an employee’s CSE or servant leadership was high.Originality/valueThe results contribute to our understanding of the relationship between challenge stressor and creativity in the big data era. Specifically, relying on the job demands–resources model, this study empirically opens the “black box” between challenge stressors and creativity by exploring two opposing intermediate mechanisms. In addition, this study reveals boundary conditions by investigating dispositional and contextual factors that can accentuate the positive effect while attenuating the negative effect of challenge stressors on employee creativity.

scholarly journals Exploring the relationship between leadership and followership of Chinese project managers

2019 ◽  
Vol 13 (3) ◽  
pp. 616-647
Author(s):  
Haoran Li ◽  
Zhenzhi Zhao ◽  
Ralf Müller ◽  
Jingting Shao
Keyword(s):  
Design Methodology ◽  
Project Managers ◽  
Content Type ◽  
Leaders And Followers ◽  
Predicting Behavior ◽  
New Perspective ◽  
Nation Wide Survey ◽  
Relationship Of ◽  
The Relationship ◽  
Selection Of

Purpose Followership is the free will recognition of leadership in the commitment toward realization of the collectively adopted organization vision and culture. The purpose of this paper is to identify the relationship between project managers’ leadership and their followership. Most project managers are both leaders and followers at the same time, but research typically investigates only their leadership. This ignores followership as an important aspect in understanding and predicting behavior, and further in the selection of project managers. Design/methodology/approach The method used for this paper is the explanatory in nature and a deductive approach, within which the above research hypothesis is tested through quantitative techniques. Data are collected through a nation-wide survey in China. Data analysis was done through factor analysis, canonical correlation analysis and multiple regression analysis. Findings The results show that transformational leadership is positively correlated with transformational followership and transactional followership, and that transactional leadership is negatively correlated with transactional followership. Research limitations/implications The paper supports a deeper investigation into leadership and followership theories. A model for both leadership and followership is developed. The findings from this paper will guide organizations to choose the project managers. Originality/value The originality lies in the new way to examine the relationship between leadership and followership. It is the first study on the relationship of project managers. Its value is new insights, which introduced a new perspective to understand leadership and followership.

Mediating influence of time management on the relationship between adult attention deficit and the operational effectiveness of project managers

2016 ◽  
Vol 35 (8) ◽  
pp. 970-984 ◽  
Author(s):  
Graeme Coetzer ◽  
Godfrey Gibbison
Keyword(s):  
Project Management ◽  
Attention Deficit ◽  
Time Management ◽  
Project Managers ◽  
Self Report ◽  
Future Research ◽  
Operational Effectiveness ◽  
Content Type ◽  
Potential Benefits ◽  
The Relationship

Purpose The purpose of this paper is to examine the relationship between adult attention deficit (AAD) and the operational effectiveness of project managers (OEPM) as mediated by time management (TM). Design/methodology/approach In total, 104 actively employed business graduate students each had the opportunity to be a project manager within a project team. Each team member rated the others on their operational effectiveness, completed a self-report measure of TM and identified a close associate who completed an observer version of the Brown Adult Attention Deficit Scale. The Sobel and Hayes tests were used to test the hypothesis that TM mediates the relationship between AAD and OEPM. Findings AAD is negatively associated with TM and OEPM, and TM is positively associated with OEPM. TM partially mediates the relationship between AAD and OPME. Research limitations/implications Future research requires a sample of project managers drawn directly from the workplace, and needs to examine the association of AAD with a wider set of project conditions and associated competencies to identify potential benefits and challenges. An updated and validated measure of both TM and the OEPM is required in future research. Practical implications Individuals and organizations wanting to ensure timely and successful completion of key tasks and projects need to be aware of the potentially constraining influence of AAD on TM and OPME. Relatively more intensive time and project management training is suggested for disordered project managers and team members. The use of organizational coaches and peer coaching within project teams represents a potential opportunity for distributing the potential benefits of the disorder while managing the challenges. Employee assistance programs that raise awareness and provide access to assessment are an important part of multi-modal management of the disorder in the workplace. Social implications Employers are facing increasing social, legal and economic pressures to support functional but disordered employees, be more inclusive and take appropriate advantage of employee diversity. This research provides constructive suggestions for how to support disordered employees with project management responsibilities. Originality/value This research study is the first examination of the relationships between AAD, TM and OEPM, and is of value to researchers, organizational development specialists, human resource management specialists, managers and employees who are seeking effective multi-modal management of the disorder in the workplace.

Quality dominant logic in big data analytics and firm performance

2019 ◽  
Vol 25 (3) ◽  
pp. 512-532 ◽  
Author(s):  
Samuel Fosso Wamba ◽  
Shahriar Akter ◽  
Marc de Bourmont
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Data Analytics ◽  
Online Survey ◽  
Information Quality ◽  
Big Data Analytics ◽  
Firm Strategy ◽  
Theoretical Understanding ◽  
Content Type ◽  
The Relationship

Purpose Big data analytics (BDA) gets all the attention these days, but as important—and perhaps even more important—is big data analytics quality (BDAQ). Although many companies realize a full return from BDA, others clearly struggle. It appears that quality dynamics and their holistic impact on firm performance are unresolved in data economy. The purpose of this paper is to draw on the resource-based view and information systems quality to develop a BDAQ model and measure its impact on firm performance. Design/methodology/approach The study uses an online survey to collect data from 150 panel members in France from a leading market research firm. The participants in the study were business analysts and IT managers with analytics experience. Findings The study confirms that perceived technology, talent and information quality are significant determinants of BDAQ. It also identifies that alignment between analytics quality and firm strategy moderates the relationship between BDAQ and firm performance. Practical implications The findings inform practitioners that BDAQ is a hierarchical, multi-dimensional and context-specific model. Originality/value The study advances theoretical understanding of the relationship between BDAQ and firm performance under the influence of firm strategy alignment.

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