Search results

The purpose of this paper is to empirically examine the perspective of youth employees about owner manager businesses. The owner-manager business (a one-man business) is the most common in Lagos. Hence, an inquiry into their management style and how it impacts youth employees within the context of decent work is important to explore.

The study used the convenience sample technique to obtain data from 382 owner-managers and youth employees who work in owner-managed businesses across various sectors. They were administered a questionnaire with carefully structured questions, with an 81% return rate. The exploratory factor analysis (EFA) technique was used to identify the prominent parameters, and the hypothesis tested and validated accordingly.

The study identified three prominent factors that youth consider when working for an owner-manager business, i.e. the workplace factor, geographical factors and employee benefit. Consequently, issues regarding sustainable employment, conducive working conditions, job security and pension are paramount in the youths' view. Many owner-managers do not respect labour laws, and job security is low in owner-managed businesses; hence, they experience high turnover as most youth work in one-man businesses to gain experience.

The owner-manager business is the most predominant in the country and yet is under-researched. Furthermore, the perception of youth employees regarding owner-manager businesses provides a better understanding of performance and expected satisfactory outcome required from youth employees and how they can be met through proper channelling of their energies to the right tasks.

This study aims to introduce the perceived systems intelligence (SI) inventory, developed based on the earlier published self-report SI inventory (Törmänen et al., 2016). It can be used together with earlier managerial level tools for building a learning organization and included in general 360-style evaluations in personnel development.

The inventory is validated with confirmatory factor analysis with a model based on the self-report SI inventory, using data from full-time used employees and managers in the USA and UK. Perceived SI factor scores are correlated with the perceived study performance of the individual.

The perceived SI inventory is found to have good factorial validity, and it correlates strongly with evaluations of perceived study performance. Managers perceived high in performance are also found to score high in perceived SI. Perceived SI does not depend on gender, age, organization size or industry.

The perceived SI inventory is the first personnel level peer evaluation tool suggested for developing learning organizations. The new inventory makes peer evaluations possible and provides a new grassroots level tool for personnel development programs in learning organizations.

While many studies in family business research focus on mono-causal impacts of succession, the purpose of this paper is to employ a systemic approach to analyze dynamic effects of intra-family succession on multiple business areas in family-run companies.

A system analysis using a participatory approach was conducted for a reference family-run company operating in the horticultural retail sector in Germany. The Vester Sensitivity Model, supplemented with principles from system thinking was used to identify key variables related to intra-family succession.

Expert input and analysis of variable co-occurrence revealed key variables associated with succession such as “strategic planning,” “productivity” and “financial flexibility.” Dynamic interactions among various business areas were identified by simulating interventions in succession trajectories. In particular, key variables such as “conflicts between family and work” and “organizational climate” turned out to be highly sensitive to changes during a succession process.

The concept and design of this system analysis tool will allow practitioners such as company managers and business consultants to better understand complex interrelations within companies and provide additional guidance with regard to critical events like business transfer.

The present study uses system thinking to analyze succession and its dynamic and time-lagged impacts on affected business areas in family-run companies for the first time. Repeated application of the systemic approach presented here to real-world business cases will gradually improve the tool and the quality of information it provides.

This paper aims to analyze unexplored connections between economic, environmental and social dimensions of corporate social responsibility (CSR) and knowledge management (KM) strategies (exploration, exploitation), also considering environmental dynamism as an influencing variable on these connections. The predicted CSR-KM interplay suggests, from stakeholder and knowledge-based views of the firm, the existence of ideal configurations between CSR and KM strategies that generate differentiated impacts on companies’ innovation capabilities, especially in dynamic environments.

Structural equation modeling by means of the partial least squares technique was used to test the study’s hypotheses after collecting survey data from Spanish companies of the renewable energy sector.

The study findings show that in highly dynamic environments, companies will tend to commit prominently in CSR, although their orientation (economic, environmental, social) and effects on innovation capabilities will depend mainly on the selected KM strategies. Social and environmental CSR are found to be highly related to KM exploration, whereas economic CSR is highly related to KM exploitation. Nevertheless, while a significant indirect effect of economic CSR by means of the KM exploitation strategy on innovation capabilities is found, the proposed indirect effect of both environmental and social CSR through the KM exploration strategy on innovation capabilities is not significant.

The results suggest that company managers should be aware of the advantages of following specific paths of investment in KM and CSR initiatives in highly dynamic environments, as there is a potential payoff in terms of innovation capability improvement. The results also suggest that “good” relationships with stakeholders, built from specific CSR investments, make firms able to get valuable knowledge that it is useful to develop KM strategies for innovation capability development.

Previous studies do not consider the interplay between KM strategies and CSR as a catalyzer for developing a firm’s innovation capabilities. This paper contributes to the KM and innovation literatures by introducing CSR into the conversation about how to improve innovation capabilities in dynamic and sustainable industries by using configurations of KM strategies and specific CSR investments in economic, social and environmental areas.

The era of crowd network is coming and the research of its steady-state is of great importance. This paper aims to establish a crowd network simulation platform and maintaining the relative stability of multi-source dissemination systems.

With this simulation platform, this paper studies the characteristics of “emergence,” monitors the state of the system and according to the fixed point judges the system of steady-state conditions, then uses three control conditions and control methods to control the system status to acquire general rules for maintain the stability of multi-source information dissemination systems.

This paper establishes a novel steady-state maintenance simulation framework. It will be useful for achieving controllability to the evolution of information dissemination and simulating the effectiveness of control conditions for multi-source information dissemination systems.

This paper will help researchers to solve problems of public opinion control in multi-source information dissemination in crowd network.

Many firms struggle to implement strategies that can successfully enhance the environmental sustainability of their processes. Drawing on the theories of green intellectual capital and complementary assets, this study develops a model describing the mechanism whereby firms can translate a green (i.e., environmental) strategy into a superior green process innovation performance (GPIP).

Regression analysis of multi-source survey data collected from 514 managers at 257 firms (257 top management members and 257 safety or environmental managers) was used to test the hypotheses.

A firm's green strategic intent has positive effects on the three aspects of green intellectual capital (i.e., human, organizational and relational capital). In turn, these three aspects have positive effects on GPIP. Moreover, green organizational capital positively moderates the effect of green relational capital on GPIP, whereas it negatively moderates the effect of human capital on GPIP.

In order to implement a green strategy successfully, especially in polluted industries such as the chemical industry, managers need to develop not only the firm's tangible resources but also its intangible resources. The more they invest in green organizational capital, the higher the level of GPIP that can be achieved. On average, a firm's green human capital is more important than its organizational and relational capital. Moreover, its organizational capital helps capture the benefits of its relational capital, but it impairs the creativity of its human capital.

The authors contribute to the literature on green strategy implementation by suggesting that green intellectual capital plays a mediating role in the relationship between a firm's green strategic intent and GPIP.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this paper is to provide the extensive review on dynamic monitoring of forestry area in China.

Countermeasure and suggestions were proposed for three aspects including the establishment of data sets with unified standards, top-level design of monitoring and assessment and analysis models, and establishment of the decision support platform with multiple scenario simulation.

Finally, the authors proposed key research area in this field, i.e., improving the systematic and optimal forest management through integrating and improving the data, models and simulation platforms and coupling the data integration system, assessment system and decision support system.

The authors explored the limitation of dynamic monitoring and state of the art research on data accumulation, professional model development and the analytical platform.

This paper aims to focus on conditions for workplace learning (WPL) in highly transient workplaces, exemplified by the tourism and hospitality sector in the Arctic region. The aim is to analyse and discuss how employees and employers view the conditions for employees’ WPL from their respective perspectives.

The study is based on a qualitative approach. Ten interviews with employers and ten interviews with employees were carried out. This opens for different perspectives, including identifying “learning gaps”. The analysis was thematic, with a focus on opportunities and challenges for WPL in these transient workplace contexts.

Overall, conditions for WPL seem unsatisfactory. On the one hand, both employees and employers see WPL as essential for staff retention. Employers also see WPL as a strategy for business development and, thus, profit. On the other hand, high staff turnover makes it challenging to strategically invest in and organize for WPL, especially formal learning. Hence, a Catch-22 situation emerges.

As this study is qualitative in its scope, generalizations are analytical rather than statistical.

There is a shortage of studies on conditions for WPL, focusing particularly on transient workplaces. Moreover, by including employer and employee perspectives, the authors contribute to a gap in the literature. The empirical contribution of this paper thus lies in using a theoretical WPL framework on transient workplaces, exemplified by the tourism and hospitality industries in the Arctic region.