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The purpose of this paper is to represent the findings from the first phase of an ongoing research project whose primary goal is to identify the most significant organizational internal and external cultural variables that leverage and enable a firm’s intellectual capital (IC) to make it more competitive in the marketplace.

The authors build on their earlier work in which Ulrich’s definition of IC as Competence × Commitment was expanded to include two additional dimensions, Creativity and Culture. The previous model explored the relationship between IC and the following five critical variables: Competence, Commitment, Control, Creativity and Culture. Here, the authors identify the most significant organizational internal and external cultural variables that leverage and enable a firm’s IC to make it more competitive in the marketplace.

This paper demonstrates the interplay between different cultural types and levels of business volatility on IC. The authors argue that the more volatile the industry is, the greater the need to secure and capitalize on IC, and the more critical it is for firms to adopt a flexible and adaptive organic culture that encourages the creation and leveraging of IC.

This framework is original and expands on Ulrich’s classical work on IC. It helps senior leaders and managers explore how to effectively and proactively capitalize on IC and leverage complex IC assets. The preliminary exploration into these convergent strands has provided a foundation to further develop and establish the interrelationships between organizational culture and IC.

The purpose of this study is to both understand the motives for volunteering in local government (a strong/structured context) and determine how such motivation and other demographics interact with organisational contexts to influence volunteering outcomes.

The study adopts a functional approach to volunteerism. The Volunteer Functions Inventory is modified to better assess the motivations of elected local government volunteers. The responses of 152 Maltese local councillors were used to answer four research questions empirically.

Exploratory and confirmatory factor analyses supported the introduction of a seventh VFI dimension, namely the political function. The study provides evidence that local councillors who received greater amounts of functionally relevant benefits reported more satisfaction and a stronger intention to continue volunteering in local government. The aggregated effect of multiple motives as well as other person-based determinants (marital status and education) produced a significant impact on volunteering outcomes in this strong/structured situational context of this public sector environment.

This study contributes to a better understanding and assessment of the motivations of elected local government volunteers. It addresses practical recommendations for sustaining civil society, while acknowledging the potential and contribution of volunteers with various demographic characteristics.

This research takes Taijiang National Park (TNP) tourists as the study population while gathering the survey data via an online questionnaire. For the data analyses, it uses the importance–performance analysis (IPA) and the Kano two-dimensional quality model to evaluate the tourist satisfaction of TNP. Specifically, it considers the importance of service quality, classifies its service quality attributes, and suggests the priority for service improvement, rendering the TNP valuable reference points to realign service strategies. The study shows that the service quality attributes related to service personnel are the priority item to be improved, which could eventually enhance tourist satisfaction. In addition, brand differentiation could be achieved by improving the attractive quality items identified in this study to enhance tourist loyalty.

Community health workers (CHWs) are vital to addressing public health system limitations in developing countries. However, effective identification and support of underperforming CHWs remains a challenge. This study develops a predictive model to proactively identify underperforming CHWs, facilitating targeted interventions for improved CHW programmes.

We developed a predictive model to identify underperforming CHWs in Uttar Pradesh, India. Data from 140,101 CHWs over a 12-month period was used to build, test and validate the model. Classification techniques, ensemble modeling and a model tuning algorithm were employed for accuracy optimization and early identification.

Logistic regression, decision trees and random forests yielded the best performance. While ensemble models offered no significant performance improvements over the base models, the model tuning algorithm effectively increased prediction accuracy by 19 percentage points. This enabled early identification of poor-performing CHWs and high-risk CHW clusters early in the year.

The developed model has significant potential to improve CHW programmes. It enables targeted support, feedback and resource allocation, leading to enhanced CHW performance, motivation and healthcare outcomes in the communities they serve. The model can provide personalised feedback to help CHWs overcome challenges and dynamic clustering facilitates proactive identification and tailored support for those at risk of underperformance.

This study is the first attempt to use predictive modelling to identify underperforming CHWs, advancing the nascent field of CHW performance analytics. It underscores the effectiveness of digital technologies and data in improving CHW programmes.

The constantly evolving higher education (HE) sector is creating a need for new business models and tools for evaluating performance. In this paper, an overview of the importance-performance analysis (IPA) model and its applicability as a management tool for assessing student satisfaction in the HE sector is provided. The purpose of this paper is to apply IPA in a new and novel manner, undertaking analysis at three levels; the individual student, for individual attributes and at a construct or factor level which combines individual attributes that are correlated. A practical application is illustrated, assessing the gap between the importance placed on specific student satisfaction attributes and corresponding levels of student-perceived performance realised.

The “service product bundle” (Douglas et al., 2006) is refined based on focus group evaluation. Survey responses from 823 students studying across four Malaysian private universities are analysed using factor analysis and the IPA model utilised to identify importance-performance gaps and explore the implication of the iso-rating line as well as alternative cut-off zones.

Factor reduction of 33 original measurement items results in eight definable areas of service provision, which provides a refined and extended management tool of statistically reliable and valid constructs.

The research is undertaken in a private business school context in Malaysia. Further research could focus on other universities or countries, as well as faculties such as computing and engineering or explore other elements of education-based performance.

The research method and study outcomes can support HE managers to allocate resources more effectively and develop strategies to improve quality and increase student satisfaction.

Distinct from other IPA-based studies, analysis is undertaken at three levels; the individual participant, for individual items and at the factor level.

The purpose of this paper is to present a case study on the development of the cultural heritage sector on the island of Gozo in the Maltese archipelago. The studying of these relationships is very important to maximise the impact of the cultural heritage sector on tourism. The importance of the development of cultural tourism as a specific niche has been consistently recognised (Boissevain, 1994; Ministry for Tourism and Culture, 2007; Ministry for Tourism Culture and the Environment, 2016; Ministry for Tourism, 2014).

A case study methodology is adopted. The findings have been sourced mainly through secondary data such as official publications and materials available publicly, and through the author’s in-depth knowledge of the socio-cultural context of Gozo.

The paper’s main outcome is that the success of the cultural heritage sector in Gozo can be attributed to the close collaboration that exists between the Ministry for Gozo (responsible for Gozitan affairs) and non-governmental organisations (NGOs). While a culture of mistrust towards state institutions is generally prevalent among Gozitans (Azzopardi, 2015), the level of collaboration between the Ministry for Gozo and NGOs, may tend to show that Gozitans are more keen to trust state institutions run by the same Gozitans.

This paper analyses the underlying relationships in the cultural heritage sector on the island of Gozo. This is very important to continue building up on this niche as an added value to the tourism sector in Gozo.

This paper aims to present a methodology for the prioritization of innovations and improvements in services and products that integrates penalty–reward contrast analysis (PRCA) and improvement gap analysis (IGA).

The presented method is theoretically developed and simulated. It uses a case study with 290 clients of supermarkets, evaluating 16 attributes of this service, to demonstrate the advantages of integrating PRCA and IGA.

The integration of PRCA and IGA provides benefits that outweigh the use of each method individually. The joint use of these methods allows the identification of possible nonlinear impact of attributes on customers’ overall satisfaction, allowing managerial recommendations to be made with greater discriminatory power, in addition to qualifying the identification of innovative attributes.

Managers must be aware of the effect of the interaction of innovative attributes with attributes already used by the company. At the same time, it is appropriate to verify whether there is potential to improve the existing attributes. The literature shows that PRCA identifies the nonlinear influence of customers’ satisfaction with individual attributes on overall satisfaction, but it fails to identify the possible impact of innovative attributes. In turn, IGA identifies innovative attributes but does not identify how the attributes influence overall satisfaction. Thus, the benefits of integrating PRCA and IGA outweigh the individual limitations of each method, thereby increasing the quality of managerial recommendations. Moreover, a limitation of PRCA makes this method useful for identifying innovative attributes in relation to attractive attributes identified by the IGA method.