Importance-performance Map Analysis Research Articles

Exploring family supportive supervisor behaviours from a police perspective to ensure life satisfaction: an empirical investigation using importance-performance analysis

PurposeThe primary aim of this research is to analyse the impact of family-supportive supervisor behaviours (FSSB) on the level of life satisfaction among individuals working in the police force. FSSB is informal support by supervisors, which is an emerging topic. Further, this study examines the intermediary role of career calling and job embeddedness in the association between supportive family behaviours of supervisors and life satisfaction. However, only limited studies have been conducted on how informal support by the supervisor performs for police personnel. This research aims to fill this gap.Design/methodology/approachFor the purpose of data collection from police personnel, we used a structured questionnaire. Variance-based partial least squares structural equational modelling (PLS-SEM) methodology was applied using SmartPLS software to investigate the conceptual model of the study. Additionally, using importance-performance map analysis (IMPA), we evaluate the importance and performance of each construct.FindingsThe data analysis findings indicate that job embeddedness and career calling function as complete mediating factors in the association between FSSB and life satisfaction. Additionally, the study revealed that career calling is the most performing construct for promoting life satisfaction but is not perceived as important by the police department.Originality/valueAccording to the authors’ knowledge, there has been no research in the Indian context that examines the effects of supervisor family supportive behaviours, especially among police. The incorporation of career calling and job embeddedness as mediators provides a novel perspective in the examination of the correlation between FSSB and life satisfaction.

The hustle behind knowledge: role of workplace ostracism and knowledge hiding towards quiet quitting in knowledge-intensive organisations

Purpose Given the workplace’s reinvention to accommodate the global pandemic’s novel conditions, knowledge hiding (KH) behaviour in knowledge-intensive organisations must be examined from a fresh perspective. In this context, the relationship between workplace ostracism (WO) as KH’s antecedent and quiet quitting (QQ) as its consequence is undertaken via the mediating role of KH behaviour among knowledge workers (KWs). Design/methodology/approach Through stratified sampling, data from 649 KWs is obtained to test the model. Partial least squares structural equation modelling (PLS-SEM) using SMART-PLS 4.0. software establishes a significant influence of WO on KH and QQ. KH significantly mediates the relationship between WO and QQ, highlighting its critical intermediary role PLSPredict evaluates the model’s predictiveness. WO and KH’s effects on QQ are examined using necessity logic by collectively applying PLS-SEM and necessary condition analysis (NCA). Findings The model wherein WO plays a significant role in increasing KH and QQ, with KH as a partial mediator in the relationship, has high predictive relevance. Moreover, NCA confirms WO as the key predictor variable that provides variance in QQ, followed by KH. The Importance-performance map analysis technique supports the study’s managerial implications. Originality/value This study enriches QQ’s emerging literature by empirically identifying its antecedents-WO and KH. Methodologically, this paper gives a model for using PLS-SEM and NCA together in relation to QQ by identifying WO as its necessary condition. Evidence of selected constructs’ interrelationships may help organisations draft leadership programmes to curtail KH and QQ behaviour.

Based on the S–O–R theory adoption intention of blockchain technology in libraries: a two-stage analysis SEM–PLS and ANN

PurposeBlockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.Design/methodology/approachUtilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.FindingsThe research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.Originality/valueUnlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.

Memorable experiences and their influential factors: an importance-performance analysis of a cultural event

ABSTRACT This study aimed to verify the underlying influential factors of cultural event attributes and proposed a structural model to examine the event dimensions that influence attendees’ memorable experiences and subsequent life satisfaction and sharing experiences. Partial least squares structural equation modelling (PLS-SEM) was used to analyse the proposed conceptual model with data obtained from 756 respondents. The results indicated that activities, uniqueness, distinctiveness and authenticity had strong and positive effects on memorable experiences, which, in turn, impacted life satisfaction and sharing experiences via social media. An in-depth examination through importance – performance map analysis (IPMA) revealed the prioritisation of crucial event dimensional attributes.

Mobile Wallet Adoption in An Emerging Economy: An Empirical Validation of a Continuance Model

This paper proposes a continuance model of mobile wallet (m-wallet) adoption in an emerging economy. Then, the proposed model is tested using data collected from 621 m-wallet users. For data analysis, we use a partial least squares structural equation modeling tool to estimate the model and conduct multi-group analysis based on user location. An importance-performance map (IPM) analysis is also conducted. The results show that perceived user connectivity, technology characteristics, and satisfaction strongly predict m-wallet continuance intention. The multi-group analysis detected some differences based on user location. Then, the IPM analysis shows that perceived user connectivity seems to be the construct with the highest importance and performance for continuance intention. Finally, implications for research and practice are presented and discussed.

Parents’ effects on Chinese students’ digital entrepreneurship motivation on live streaming platforms: regional perspective using multi-group analysis

Purpose This paper aims to explore the effects of parents’ support factors on Chinese university students’ digital entrepreneurship motivation on live streaming platforms. Based on the Social support theory, this study divides influencing factors into emotional, instrumental, informational and appraisal aspects. Meanwhile, considering the impact of China’s regional differences, the paper refers to the Regional difference theory and performs a multi-group analysis to assess the differences based on Chinese university students’ regional backgrounds. Design/methodology/approach By testing 556 samples based on the partial least squares path modelling and variance-based structural equation modelling, all support factors parents provide can stimulate Chinese university students’ digital entrepreneurship motivation. Findings Based on the multi-group comparison, parents’ informational support exerts a more substantial influence on the digital entrepreneurship motivation for university students from central and east regions rather than those from the western region, and parents’ instrumental support exerts a lower influence on digital entrepreneurship motivation for east university students than for west university students. Originality/value This paper applies the Social support theory as a theoretical framework to divide the impact factors, and it uses the Regional difference theory as a guide for the multi-group analysis of correlations, which is significant for online entrepreneurial motivation research and a better understanding of student groups. In addition to testing the hypotheses, the study also measures the importance–performance map analysis to explore additional findings of influencing factors and discuss managerial implications.

Invisible threats: An investigation of electrical hazards and safety practices among residential electricity consumers

Understanding electrical hazards and implementing safety measures is paramount to protecting lives and property. Therefore, this research investigates electrical hazards in households and safety measures taken by residents in Sokode–Etoe, Ghana. The primary objective is to identify gaps in knowledge regarding electrical hazards among domestic electricity consumers and offer recommendations to enhance safety and mitigate the risks. The data were systematically collected from 200 participants, including both homeowners and tenants, using a structured questionnaire. The results were presented using Likert scale analysis, sample t-test, binary logistic regression analysis, involving statistical hypothesis testing of predictor variable coefficients, Importance-Performance Map Analysis (IPMA) and Necessary Condition Analysis (NCA). Participants showed a high awareness of electrical hazards, yet demonstrated a weaker grasp of safety practices, correct emergency procedures, and infrequent testing of wiring systems by homeowners. The predominant electrical accident that emerged was electrical shock. Most homeowners have not engaged certified electrical inspectors for a decade, reflecting uncertainty about the safety protocols in place. Furthermore, respondents expressed a degree of uncertainty regarding the safety measures implemented in their households concerning electricity usage. This study underscores the pressing need to raise awareness and promote safe electrical practices in residential environments. Such an educational initiative could utilize a variety of communication channels, social media influencers, renowned personalities, customised mobile applications and other platforms. This research stands out as the inaugural investigation offering a comprehensive examination of the hazards related to energy consumption and safety precautions in Ghana. It focuses on an often-overlooked demographic of electricity users in Ghana, shedding light on domestic electrical safety issues and the growing hazards.

Breaking down barriers: rationalisations and motivation to stop among Chinese male smokers under cigarette dependence

BackgroundSmoking rationalisation beliefs are a huge barrier to quitting smoking. What types of rationalisations should be emphasised in smoking cessation interventions? Although past literature has confirmed the negative relationship between those beliefs and motivation to stop smoking, little is known regarding the importance and performance of those beliefs on motivation with varying cigarette dependence. The study aimed to ascertain rationalisations that are highly important for motivation yet perform poorly in different cigarette dependence groups.MethodsThe cross-sectional study was conducted from November 19 to December 9, 2023 in Guiyang City, China. Adult male current smokers were enrolled. Partial least squares structural equation modelling was used to test the hypothesis. The multi-group analysis was used to determine the moderating effect of cigarette dependence, and the importance-performance map analysis was utilised to assess the importance and performance of rationalisations.ResultsA total of 616 adult male current smokers were analysed, and they were divided into the low cigarette dependence group (n = 297) and the high cigarette dependence group (n = 319). Except for risk generalisation beliefs, smoking functional beliefs (H1: -β = 0.131, P < 0.01), social acceptability beliefs (H3: β = -0.258, P < 0.001), safe smoking beliefs (H4: β = -0.078, P < 0.05), self-exempting beliefs (H5: β = -0.244, P < 0.001), and quitting is harmful beliefs (H6: β = -0.148, P < 0.01) all had a significant positive influence on motivation. Cigarette dependence moderated the correlation between rationalisations and motivation. In the high-dependence group, the social acceptability beliefs and smoking functional beliefs were located in the “Concentrate Here” area. In the low-dependence group, the social acceptability beliefs were also situated in there.ConclusionsSocial acceptability beliefs and smoking functional beliefs showed great potential and value for improvement among high-dependence smokers, while only social acceptability beliefs had great potential and value for improvement among low-dependence smokers. Addressing these beliefs will be helpful for smoking cessation. The multi-group analysis and the importance-performance map analysis technique have practical implications and can be expanded to other domains of health education and intervention practice.

Impact of the propensity to cross-cultural adaptation on online viewers' attitudes toward ethnic minority group cultural streaming: An extension of the theory of planned behaviour

Although more and more ethnic minority group (EMG) users are willing to present cultural content on live streaming platforms and advertise cultural products, the influence of their cultural content is still weak compared to mainstream culture. To narrow the research gap, it is essential for the current study to analyse online viewers' intention to watch EMGs' cultural content. This paper extends the Theory of Planned Behaviour (TPB) model based on the cross-cultural adaptation theory. It adds the propensity to cross-cultural adaptation factor and cross-cultural adaptation factor, aiming to clearly explain online viewers' psychological changes. The data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS- SEM) supports that the propensity to cross-cultural adaptation positively affects online viewers' cross-cultural adaptation. Meanwhile, the cross-cultural adaptation will positively influence online viewers' attitudes towards EMG cultural streaming, motivate their watching intention, and drive their final behavioural responses. More findings are uncovered via the importance-performance map analysis (IPMA), and the cross-cultural adaptation factor has significantly high performance and importance for online viewers’ watching intention.

Impact of the propensity to cross-cultural adaptation on online viewers' attitudes toward ethnic minority group cultural streaming: An extension of the theory of planned behaviour

Although more and more ethnic minority group (EMG) users are willing to present cultural content on live streaming platforms and advertise cultural products, the influence of their cultural content is still weak compared to mainstream culture. To narrow the research gap, it is essential for the current study to analyse online viewers’ intention to watch EMGs’ cultural content. This paper extends the Theory of Planned Behaviour (TPB) model based on the cross-cultural adaptation theory. It adds the propensity to cross-cultural adaptation factor and cross-cultural adaptation factor, aiming to clearly explain online viewers’ psychological changes. The data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM) supports that the propensity to cross-cultural adaptation positively affects online viewers’ cross-cultural adaptation. Meanwhile, the cross-cultural adaptation will positively influence online viewers’ attitudes towards EMG cultural streaming, motivate their watching intention, and drive their final behavioural responses. More findings are uncovered via the importance-performance map analysis (IPMA), and the cross-cultural adaptation factor has significantly high performance and importance for online viewers’ watching intention.

Analytical modeling of perceived authenticity in AI assistants: application of PLS-predict algorithm and importance-performance map analysis

PurposeThe present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.Design/methodology/approachPartial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.FindingsA positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.Practical implicationsThe findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.Originality/valueThe study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.

Combined importance–performance map analysis (cIPMA) in partial least squares structural equation modeling (PLS–SEM): a SmartPLS 4 tutorial

AbstractRecent research on partial least squares structural equation modeling (PLS–SEM) extended the classic importance–performance map analysis (IPMA) by taking the results of a necessary condition analysis (NCA) into consideration. By also highlighting necessary conditions, the combined importance–performance map analysis (cIPMA) offers a tool that enables better prioritization of management actions to improve a key target construct. In this article, we showcase a cIPMA’s main steps when using the SmartPLS 4 software. Our illustration draws on the technology acceptance model (TAM) used in the cIPMA’s original publication, which features prominently in business research.

Insights into the performance of green supply chain in the Chinese semiconductor industry

To achieve the global carbon neutrality goal by 2050, businesses are urged to take the lead in adopting sustainable practices. Recently, there has been a growing interest among both academics and practitioners in utilizing artificial intelligence (AI) for digital transformation. However, measuring the impact of digital transformation on achieving carbon neutrality goals is still in its infancy, particularly in the context of the semiconductor industry. Therefore, this study aims to explore the nexus between AI capabilities, digital transformation, and carbon neutrality in enhancing green supply chain performance. A partial least squares structural equation modeling, bootstrapping, and importance-performance map analysis were employed to test the proposed research model. The data was obtained through a structured questionnaire from 426 respondents from semiconductor firms in China. The results revealed that AI capabilities positively impact the digital transformation of Chinese semiconductor firms. Furthermore, the findings demonstrated that digitally transformed firms are better equipped to achieve carbon neutrality objectives. Lastly, the study found a positive correlation between carbon neutrality and the overall performance of green supply chains in semiconductor manufacturing firms. These results serve as a valuable resource for logistics and supply chain managers, providing insights into how AI capabilities can be harnessed to enhance the performance of green supply chains.

Measuring crowdfunding success for small and medium‐sized enterprises sustainable development: Insight from the social networking theory

AbstractWith little to no study on the effect of social networking theory on the success of a crowdfunding campaign in Africa, this study investigated some of the factors that influence the success of a crowdfunding campaign using Ghana as a case for a broader justification and generalization of findings that has been obtained in previous studies. This study identified four factors through an extensive literature review of the social networking theory. These are the number of social network handless of an entrepreneur, activeness of an entrepreneur on a social network, number of social network friends of an entrepreneur and the availability of project videos on an entrepreneur's social network. Data were then collected empirically from 462 respondents using a questionnaire. The data obtained were analyzed using the partial least square structural equation modeling. The results revealed that all the identified factors positively influence the success of a crowdfunding campaign. The study further proposes that fund seekers on the crowdfunding platform post their project information on weekends and evenings on weekdays since people pay special attention to information posted at these times. Also, the outcome of the importance performance map analysis disclosed that the number of social network handles of an entrepreneur is the most essential in terms of importance when seeking funds on the crowdfunding platform. This study provides valuable insight into how small and medium‐sized enterprises in Ghana and other stakeholders of crowdfunding platforms can use the concept of social networking theory to achieve funding success on crowdfunding platforms.

Consumers’ receptivity to mHealth technologies: a hybrid PLS–ANN approach

PurposeMobile health (mHealth) technologies, in particular, have been sought after and advocated as a means of dealing with the pandemic situation. Despite the obvious advantages of mHealth, which include monitoring and exchanging health information via mobile applications, mHealth adoption has yet to take off exponentially. Expanding on the unified theory of acceptance and use of technology (UTAUT) model, this study aims to better comprehend consumers’ receptivity to mHealth even after the pandemic has subsided.Design/methodology/approachThrough purposive sampling, data were collected from a sample of 345 mobile phone users and analysed using partial least squares structural equation modelling (PLS-SEM) and artificial neural networks (ANN) capture both linear and nonlinear relationships.FindingsEffort expectancy, performance expectancy, social influence, pandemic fear and trustworthiness positively influenced mHealth adoption intention, with the model demonstrating high predictive power from both the PLSpredict and ANN assessments.Research limitations/implicationsThe importance–performance map analysis (IPMA) results showed that social influence had great importance for mHealth uptake, but demonstrated low performance.Practical implicationsReferrals are an alternative that policymakers and mHealth service providers should think about to increase uptake. Overall, this study provides theoretical and practical insights that contribute to the advancement of digital healthcare, aligning with the pursuit of Sustainable Development Goal 3 (SDG 3) (good health and well-being).Originality/valueThis study has clarified both linear and nonlinear relationships among the factors influencing intentions to adopt mHealth. The findings from both PLS and ANN were juxtaposed, demonstrating consistent findings.

Factors Affecting Customer Satisfaction in the Retail Formats in Rupandehi

This paper aims to investigate the Factors Affecting Customer Experience in the Retail Formats In Rupandehi district of Nepal. Primary data have been collected through structured questionnaire using online method i.e. Google Forms out of 384 different retail format users district of Nepal. A descriptive Research and causal comparative design was used and sample was selected by purposive sampling method. Smart PLS 4 is used as a data analysis tool and various tests like descriptive analysis, Measurement Model Assessment, Convergent Validity and Discriminant Validity, Model Fit Assessment, Structural Model Assessment and Importance-Performance Map Analysis (IMPA) tests were conducted as analysis tool to assess the quantitative raw data. The study concludes that Price and Assortment has positive significant relationship with Customer satisfaction whereas social environment and Retail atmosphere has positive insignificant relationship with customer satisfaction.

Determinants Affecting Life Insurance Purchase Decision at Jhapa District

This paper aims to investigate the effect of determining factors like Customer Attitude, Insurance Awareness, Financial Literacy and Social Factor on purchase decision of life insurance policy in Jhapa district of Nepal. Primary data have been collected through structured questionnaire using online method i.e. Google Forms out of 384 life insurance policy holders resident of Jhapa district of Nepal. A descriptive Research and causal comparative design was used and sample was selected by purposive sampling method. Smart PLS 4 is used as a data analysis tool and various tests like descriptive analysis, Measurement Model Assessment, Convergent Validity and Discriminant Validity, Model Fit Assessment, Structural Model Assessment and Importance-Performance Map Analysis (IMPA) tests were conducted as analysis tool to assess the quantitative raw data. The study concludes that Customer Attitude, Financial Literacy, and Insurance Awareness has significant effect with the purchase decision of life insurance policy whereas Social Factor has no significant effect with the purchase decision of life insurance policy. Financial Literacy has the highest influence over purchase decision of life insurance. Thus, the marketers, policymakers and insurance companies must pay more attention in bringing more effective and fruitful programs to enhance the life insurance demand.

Customer-centric virtual reality applications adoption in the hospitality industry: quality-value-based adoption model

PurposeThe massive adoption of virtual reality (VR) applications has started since the COVID-19 pandemic, and until now, VR applications are still being used. However, there is limited research that analyses the consumer's perspective on the adoption of VR applications. Thus, this study discovers the adoption of VR applications in the hospitality sector by integrating the value-based adoption model (VAM) and VR quality.Design/methodology/approachThe data were gathered through a survey of 500 respondents and evaluated through the structural equation model-partial least squares (SEM-PLS).FindingsEmploying SEM-PLS and importance-performance map analysis (IPMA), the findings revealed that VR quality and perceived value are essential determinants in the adoption of VR applications in the hospitality industry.Practical implicationsPractically, this study encourages the hospitality industry to create and develop high-quality VR application technology to benefit visitors. Through this study, hospitality marketing managers, governments and others concerned with the hospitality industry’s future development can create effective ways to increase the adoption of VR applications in this industry.Originality/valueThis study offers novel perspectives into the theory and application of VR quality and VAM in the adoption of VR applications in the hospitality industry.

Online customer experience in Indian digital banks impacting continuous intention usage: Generation Y and Z perspective

Purpose This study aims to conceptualise a customer-centric model based on an online customer experience (OCE) construct, mediated by e-loyalty (EL) and e-trust (ET), to improve the continuous usage intention (CUI) of Indian digital banks from Generation Y and Z perspectives. Design/methodology/approach This study used an online survey method to gather data from a sample of 466 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using PLS-SEM to further study the research hypotheses. Findings The main factors that determine digital banks’ OCE are perceived enjoyment, e-service quality, information quality and e-convenience. Additionally, relevant constructs were evaluated using an importance-performance map analysis. Research limitations/implications This study used convenience sampling for the urban population using digital banking; therefore, the outcome may be generalised to a limited extent. It would be valuable to imitate studies in other countries to strengthen digital banking further. Originality/value There is a lack of research on digital banking and OCE in India; thus, this study helps rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between OCE, EL, ET and the bottom line of financial institutions, using these factors as dependent variables instead of traditional measures.

A Structural Equation Model Study for Adoption of Internet of Things for the Growth of Manufacturing Industries in Australia

This research study delves into the integration of IoT within the Australian manufacturing sector, analyzing five key factors influencing adoption and drawing comparisons with Rogers' innovation theory. Its objectives encompass assessing how competitiveness, regulatory support, management support, manufacturing growth, and cost savings affect IoT adoption. Methodologically, the research journey includes defining the problem, conducting a thorough literature review, crafting a research proposal, executing pilot and main studies, validating findings, and ultimately composing the final thesis. Quantitative data obtained from a large pool of over 500 respondents shed light on the positive impacts of competitiveness, regulatory support, and cost savings on IoT adoption. Additionally, the study employs Importance-Performance Map Analysis (IPMA) to underscore the significance of management support in successful IoT implementation. Despite facing limitations such as common method bias and constraints on generalizability, the research underscores the transformative potential of IoT in enhancing operational efficiency and decision-making within Australian manufacturing. Overall, the study's findings confirm the significant influence of key factors on IoT adoption, affirming its potential to drive competitiveness, regulatory compliance, cost efficiency, and growth within the Australian manufacturing landscape.