Gamification and gigification: A multidimensional theoretical approach

Behl, Abhishek; Jayawardena, Nirma Sadamali; Ishizaka, Alessio; Gupta, Manish; Shankar, Amit

doi:10.1016/j.jbusres.2021.09.023

Cited by 61 publications

(55 citation statements)

References 126 publications

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“…Organisations use several innovative and advanced technologies to make human resource management systems (HRMSs) more efficient and effective (Al-Harazneh and Sila, 2021). The use of information technology in managing human resources within organisations enhances the organisations' performance, employee satisfaction and helps organisations achieve competitive advantages (Marler and Boudreau, 2017;Behl et al, 2021;Luqman et al, 2021;Nusrat et al, 2021). Hence, significant changes have been witnessed in managing human resource management.…”

Section: Introductionmentioning

confidence: 99%

Explaining resistance intention towards mobile HRM application: the dark side of technology adoption

Shankar

Nigam

2021

IJM

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PurposeThe mobile human resource management application (mHRM app) has recently been seen as an innovative cloud-based solution to manage human resource management (HRM) within organisation. Despite its great potential, organisations have shown resistance towards the usage of the mHRM app. This study investigates the dark side of electronic HRM (eHRM) by examining factors affecting HR professionals' resistance to the mHRM app using status quo bias (SQB) theory. The study also examines the moderating effect of personal innovativeness.Design/methodology/approachResponses were collected from 239 HR professionals using an online survey. Structural equation modelling (SEM) and PROCESS macro were used to examine the hypotheses.FindingsThe results indicated that regret avoidance, inertia, switching costs and perceived threat significantly affect HR professionals' resistance towards mHRM app adoption. Results also indicated that high personal innovativeness negatively moderates the association between inhibitors and resistance to adopt the mHRM app.Practical implicationsThe study's findings will help HR professionals reduce their resistance towards mHRM app adoption.Originality/valueThis study enriches eHRM, mobile applications and the SQB literature.

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Section: Introductionmentioning

confidence: 99%

Explaining resistance intention towards mobile HRM application: the dark side of technology adoption

Shankar

Nigam

2021

IJM

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“…Thus, students seek new technologies that they can use for different purposes. Behl et al [37] referred the acceptance of the gamification concept to the acceptance of the whole environment (e-learning environment), since there is a link between the concept of gamification and technology, as it plays a vital role in facilitating gamification features. In particular, the use of gamified learning environments is still a sensitive subject for many educational systems [38,39].…”

Section: Gamification and Technology Acceptancementioning

confidence: 99%

To Use or Not to Use: Impact of Personality on the Intention of Using Gamified Learning Environments

et al. 2022

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Technology acceptance is essential for technology success. However, individual users are known to differ in their tendency to adopt and interact with new technologies. Among the individual differences, personality has been shown to be a predictor of users’ beliefs about technology acceptance. Gamification, on the other hand, has been shown to be a good solution to improve students’ motivation and engagement while learning. Despite the growing interest in gamification, less research attention has been paid to the effect of personality, specifically based on the Five Factor model (FFM), on gamification acceptance in learning environments. Therefore, this study develops a model to elucidate how personality traits affect students’ acceptance of gamified learning environments and their continuance intention to use these environments. In particular, the Technology Acceptance Model (TAM) was used to examine the factors affecting students’ intentions to use a gamified learning environment. To test the research hypotheses, eighty-three students participated in this study, where structural equation modeling via Partial Least Squares (PLS) was performed. The obtained results showed that the research model, based on TAM and FFM, provides a comprehensive understanding of the behaviors related to the acceptance and intention to use gamified learning environments, as follows: (1) usefulness is the most influential factor toward intention to use the gamified learning environment; (2) unexpectedly, perceived ease of use has no significant effect on perceived usefulness and behavioral attitudes toward the gamified learning environment; (3) extraversion affects students’ perceived ease of use of the gamified learning environment; (4) neuroticism affects students’ perceived usefulness of the gamified learning environment; and, (5) Openness affects students’ behavioral attitudes toward using the gamified learning environment. This study can contribute to the Human–Computer Interaction field by providing researchers and practitioners with insights into how to motivate different students’ personality characteristics to continue using gamified learning environments for each personality trait.

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“…Hence, if gig platforms are unable to give social security and other benefits to its gig workers, government should help these workers by fixing their basic salaries and securing their jobs under various labour law schemes. Introducing gamified elements by the gig platforms would also help in improving the productivity of work, become intrinsically motivated and their engagement would help in retaining the gig workforce in their jobs (Behl et al, 2021(Behl et al, , 2022.…”

Section: Managerial and Theoretical Implicationsmentioning

confidence: 99%

Barriers to entry of gig workers in the gig platforms: exploring the dark side of the gig economy

Behl

Rajagopal

Sheorey

et al. 2022

AJIM

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PurposeThe alternative arrangements to traditional employment have become a promising area in the gig economy with the technological advancements dominating every work. The purpose of this paper is to explore the barriers to the entry of gig workers in gig platforms pertaining to the food delivery sector. It proposes a framework using interpretive structural modelling (ISM) for which systematic literature review is done to extract the variables. This analysis helps to examine the relationship between the entry barriers to gig platforms. The study further proposes strategies to reduce the entry barriers in gig sector which would help to enhance productivity and generate employment opportunities.Design/methodology/approachThe study uses interpretive structural model (ISM) to ascertain the relationship between various entry barriers of the gig workers to the gig platforms. It also validates the relationship and understand the reasons of their association along with MICMAC analysis. The model was designed by consulting the gig workers and the experts allied to food delivery gig platforms namely Zomato and Swiggy.FindingsIt was observed that high competition, longer login hours and late-night deliveries are the significant barriers with high driving power and low dependence power. Poor payment structures and strict terms and conditions for receiving the incentives are interdependent on each other and have moderate driving and dependence power. The expenses borne by the gig workers, such as Internet, fuel and vehicle maintenance expenses have high dependence power and low driving power. Hence, they are relatively less significant than other barriers.Research limitations/implicationsThe study is confined to food delivery sector of India, without considering other important sectors of gig economy for generalizing the framework. As the study is based on forming an ISM framework through literature review only, it does not consider other research methods for analysing the entry barriers to the gig platforms.Practical implicationsThe study attempts to dig out the low entry barriers for gig workers in food delivery platforms as there is a dearth of analysis of these factors. This study would weave them using ISM framework to help the gig platforms overcome these barriers at various levels, thus adding to the body of literature.Originality/valueThe study discusses the need for understanding relationship between the entry barriers in the form of ISM model to identify the dependent and driving factors of the same.

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Gamification and gigification: A multidimensional theoretical approach

Cited by 61 publications

References 126 publications

Explaining resistance intention towards mobile HRM application: the dark side of technology adoption

Explaining resistance intention towards mobile HRM application: the dark side of technology adoption

To Use or Not to Use: Impact of Personality on the Intention of Using Gamified Learning Environments

Barriers to entry of gig workers in the gig platforms: exploring the dark side of the gig economy

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