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.

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.

Davenport and Prusak on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 7-11 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Data Analytics ◽  
Design Methodology ◽  
Big Data Analytics ◽  
Early Years ◽  
Content Type ◽  
Potential Risks ◽  
The Relationship

Purpose Larry Prusak and Tom Davenport have long been leading voices in the knowledge management (KM) field. This interview aims to explore their views on the relationship between KM and big data/analytics. Design/methodology/approach An interview was conducted by email with Larry Prusak and Tom Davenport in 2015 and updated in 2016. Findings Prusak and Davenport hold differing views on the role of KM today. They also see the relationship between KM and big data/analytics somewhat differently. Davenport, in particular, has much to say on how big data/analytics can be best utilized by business as well as its potential risks. Originality/value It is important to understand how two of the most serious KM thinkers since the early years of KM understand the relationship between big data/analytics, KM and organizations. Their views can help shape thinking in these fields.

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.

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamad Bahrami ◽  
Sajjad Shokouhyar
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Culture

PurposeBig data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.Design/methodology/approachThe study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.FindingsThe results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.Originality/valueThe present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

Institutional effect on born global firms in China: the role of Sun Tzu’s The Art of War strategies

2016 ◽  
Vol 10 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Man Zhang ◽  
Qian Gao ◽  
Jane V. Wheeler ◽  
Jungsook Kwon
Keyword(s):  
Emerging Markets ◽  
Institutional Environment ◽  
Critical Role ◽  
Born Global ◽  
Internationalization Process ◽  
Content Type ◽  
International Performance ◽  
The Relationship ◽  
Born Global Firms

Purpose – This paper aims to investigate the role of Sun Tzu’s significant strategies on the relationship between the institutional environment and international performance of Chinese born global firms, a type of small- and medium-sized enterprise (SME) characterized by the company’s limited resources and its early efforts to internationalize. Design/methodology/approach – The methodology is based on a multi-case analysis of interviews conducted with four chosen born global firms, coupled with public database and Web site searches. Through the use of qualitative methods, propositions were developed. Findings – This paper provides insights regarding how the institutional environment, both formal and informal, has a strong positive relationship with born global firm’s international performance. Moreover, Sun Tzu’s significant strategies play a critical role in the internationalization process of born global firms in emerging markets. Originality/value – Although existing studies discuss the application of Eastern philosophical strategies adopted by firms in emerging markets, to the best of our knowledge, this is one of the earliest studies which evaluates the moderation effect of Sun Tzu’s significant strategies on the relationship between institutional environment and business performance. The paper contributes to scholarly discourse on the influencing factors of born global firm’s internationalization process. It also has practical relevance to international entrepreneurs and SMEs from emerging markets.

Indian study shows that encouraging knowledge sharing at work can help spark innovative behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Keyword(s):  
Explicit Knowledge ◽  
Manufacturing Sector ◽  
Critical Role ◽  
Underlying Mechanism ◽  
Innovative Behavior ◽  
Content Type ◽  
Indian Manufacturing Sector ◽  
Implicit And Explicit ◽  
The Relationship

Purpose The authors wanted to find out the most important mechanisms for encouraging innovative behavior in the Indian manufacturing sector. Design/methodology/approach The researchers collected data from Indian manufacturing organizations. They distributed questionnaires and received 288 complete ones. Items measured critical concepts. For OJ one example was “I have been fairly rewarded for the effort I put forth”. For KS, one sample was, “When I have learned something new, I tell my colleagues about it” and, “When they have learned something new, my colleagues tell me about it”. Meanwhile, IB was measured using items such as “I generate original solutions for problems”. Findings It highlighted the pivotal role of OJ in bolstering employees’ IB. When companies treat employees fairly, it encourages positive social interactions that lead to perceptions of supportiveness and trustworthiness. Employees reciprocate these sentiments with positive behavior. The study also showed the positive predictive influence of KS on IB. Finally, the results showed that the relationship between OJ and IB is complex, but KS is a pivotal mediator. Promotion of OJ, KS and IM is “vital” to spark innovation. Originality/value The authors felt their most important finding was to highlight the critical role of the underlying mechanism of KS, which is where individuals exchange implicit and explicit knowledge to create new knowledge. In addition, previous researchers have looked at the role of organizational justice in encouraging innovative behavior, but evidence from non-Western countries is scarce.

Assessing the role of product category involvement and relationship proneness in the satisfaction–loyalty link in retailing

2019 ◽  
Vol 48 (2) ◽  
pp. 207-226 ◽  
Author(s):  
Choukri Menidjel ◽  
Abderrezzak Benhabib ◽  
Anil Bilgihan ◽  
Melih Madanoglu
Keyword(s):  
Relationship Marketing ◽  
Customer Loyalty ◽  
Purchase Intention ◽  
Critical Role ◽  
Product Category ◽  
Retail Industry ◽  
Mediating Effects ◽  
Content Type ◽  
The Relationship

Purpose Product category involvement and relationship proneness are crucial in explaining relationship outcomes. Nevertheless, the authors know little about their roles in the formation of loyalty, especially in the retail industry. Individual consumer traits and preferences are likely to play a critical role in the success of relationship marketing. Yet, relationship marketing studies have fallen short of considering such individual differences. The purpose of this paper is to examine the mediating effects of product category involvement and relationship proneness on the relationship between satisfaction and loyalty in retail clothing stores. Design/methodology/approach Data were obtained using a survey of 220 consumers. Partial least squares structural equation modeling was employed to test the proposed theoretical model. Findings The results show that satisfaction significantly affects product category involvement and relationship proneness, which, in turn, significantly affect purchase intention and word-of-mouth (WOM). The results also show that product category involvement and relationship proneness partially mediate the impact of satisfaction on purchase intention and WOM. Research limitations/implications Product category involvement and relationship proneness play a critical role in explaining the satisfaction–loyalty link. Future research could consider the role of potential moderating variables. Practical implications Retail managers should not only focus on improving customer satisfaction to achieve customer loyalty, but should also consider the importance of product category involvement and relationship proneness, and their role in the formation of customer loyalty both in traditional and online environments. Originality/value To the best of the authors’ knowledge, this study is the first to explore the mediating effects of product category involvement and relationship proneness on the relationship between satisfaction, purchase intention and WOM in the retail industry.

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.

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.

Big data analytics adoption model for small and medium enterprises

2020 ◽  
Vol 11 (4) ◽  
pp. 483-513 ◽  
Author(s):  
Parisa Maroufkhani ◽  
Wan Khairuzzaman Wan Ismail ◽  
Morteza Ghobakhloo
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Structural Equation ◽  
Small And Medium Enterprises ◽  
Big Data Analytics ◽  
Mediation Effect ◽  
Unified Framework ◽  
Content Type ◽  
Medium Enterprises ◽  
The Relationship

Purpose Big data analytics (BDA) is recognized as a turning point for firms to improve their performance. Although small- and medium-sized enterprises (SMEs) are crucial for every economy, they are lagging far behind in the usage of BDA. This study aims to provide a single and unified model for the adoption of BDA among SMEs with the integration of the technology–organization–environment (TOE) model and resource-based view. Design/methodology/approach A survey of 112 manufacturing SMEs in Iran was conducted, and the data were analysed using structural equation modelling to test the model of this study. Findings The results offer evidence of a BDA mediation effect in the relationship between technological, organizational and environmental contexts, and SMEs performance. The findings also demonstrated that technological and organizational elements are the more significant determinants of BDA adoption in the context of SMEs. In addition, the result of this study confirmed that BDA adoption could enhance the financial and market performance of SMEs. Practical implications Providing a single unified framework of BDA adoption for SMEs enables them to appreciate the importance of most influential elements (technology, organization and environment) in the adoption of BDA. Also, this study may encourage SMEs to be more willing to use BDA in their businesses. Originality/value Although there are studies on BDA adoption and firm performance among large companies, there is a lack of empirical research on SMEs, in particular, based on the TOE model. SMEs differ from large companies in terms of the availability of resources and size. Therefore, this study aimed to initiate a conceptual framework of BDA adoption for SMEs to assist them to be able to take advantage of the adoption of such technology.

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