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In this paper, the authors attempt to understand how labour market attachment during the ages of 30–59 influences individuals' transition out of the labour market.

Using high-quality Swedish register data, the authors follow individuals born in 1950 and observe their labour market attachment during mid-life and their exit from the labour market.

The authors find evidence that labour market attachment in different stages of the career is differently related to exit from the labour market. At the age of 30, as well as between the ages 50–59, low attachment is related with earlier exit from the labour market. On the contrary, low labour market attachment during the ages 40–49 is related with later exit from the labour market. However, regardless of age, lower labour market attachment increases the risk of work-related benefit receipt in the exit year. The authors also find evidence that gender, migration status and childhood socioeconomic disadvantages may represent obstacles to longer working lives, while high education is a consistent factor in avoiding early exit from the labour market.

This study provides insights on the link between labour market attachment in different stages of the career and the exit from the labour market as well as work-related benefits dependency in the year of exit.

Driven by the aim to increase the participation of older people in the labour force and to extend people's working lives, the Swedish Parliament passed a bill in 1998 to increase the pension eligibility age from 60 to 61 years and establish a notional defined-contribution (NDC) plan. In this article, the authors investigate the impacts towards the prolongation of working lives expected from such an intervention.

The authors apply a multinomial probabilistic model based on Swedish registry data on the birth cohorts 1937–1938 (n = 102,826) and observe differences in exit behaviour between eligible and non-eligible individuals.

The authors find that the cohorts eligible to the pension reform exit the labour market at a later age compared to non-eligible cohorts at the 61-years cut-off. The authors also find that the effect persists in the long term. Furthermore, the authors find that both men and women are equally struck by the reform.

While there exist many descriptive reports and theoretical analyses on the costs and benefits of pension reforms, this study is the first one to empirically analyse the effect of the first European NDC pay-as-you go pension plan on the potential exclusion of old-aged workers.

The purpose of this paper is to investigate the relationship among ownership structure, information disclosure and benefits of control under Lab‐experimental frame, based on the ownership structure in China's stock market.

Theoretical Shapley value of shareholders was used as the representative of control right, and benefits of control in different experimental treatments were studied.

Experimental results show: first, more counterbalance of shareholders' control rights, less benefits of their control right. Accordingly, more chance to form core alliance for the major shareholder with small shareholders, less chance for them to get control right; second, the effect of information on benefits of control are mainly reflected in forming and maintaining the alliance; third, Shapley value of the major shareholder and the information determine the alliance type; fourth, control premium may be the cost of keeping the major shareholder's benefits safe and fifth, imperfect information is not always bad, concealing information partly can improve the distribution efficiency of a corporation.

The paper provides experimental analysis of the behavioral logic behind the benefits of control, which would help to explain the relationship among ownership structure, information disclosure and benefits of control.

The purpose of this paper is to propose an integrated fuzzy approach to determine important universal usability problems (UUPs) by providing experts who behave like real users and to establish a work plan to correct the most important ones.

In this study, a fuzzy multi-criteria decision-making approach with three stages is proposed for the evaluation of universal usability. At the first stage, UUPs are identified by performing modified heuristic evaluation, and severity rating of each problem is determined by experts. At the second stage, critical problems are specified by applying the fuzzy Delphi considering these severity ratings. At the third stage, Fuzzy Decision Making Trial and Evaluation Laboratory approach is applied to prioritize critical problems as sub and main criteria. An illustrative example related to emergency service is performed to apply the proposed approach.

Results showed that the elevator button design, the elevator emergency button design and the position of the floor signboard are the first three problems that should be primarily improved as sub-criteria. In terms of main criteria, equitable use, simple and intuitive use, and perceptible information are the first three main criteria that should be improve in emergency service.

This study is original in terms of methodology and providing a new perspective for building design evaluation. The results can help the designers to see the UUPs in buildings, to focus the most important UUPs and to establish improvement ranking. These advantages provide time and cost-effective design improvement actions.

The development of green economy is of academic and policy importance to governments and policymakers worldwide. In the light of the necessity of renewable energy to sustain green economic growth, this study aims to examine the relationship between renewable energy consumption and green economic growth, controlling for the impact of trade openness for Organization for Economic Co-operation and Development countries over the period 1990-2015, within a multivariate panel data framework.

To investigate the long-run relationship between variables, panel cointegration tests are performed. Panel Granger causality based on vector error correction models is adopted to understand the short- and long-run dynamics of the data. Furthermore, ordinary least square (OLS), dynamic OLS and fully modified OLS methods are used to confirm the long-run elasticity of green growth for renewable energy consumption and trade openness. Moreover, system generalized method of moment is applied to eliminate serial correlation, heteroscedasticity and endogeneity problems. The authors used the panel Granger causality test developed by Dumitrescu and Hurlin (2012) to infer the directionality of the causal relationship, allowing for both the cross-sectional dependence and heterogeneity.

The results suggest that renewable energy consumption and trade openness exert positive effects on green economic growth. The results of long-run estimates of green economic growth reveal that the long-run elasticity of green economic growth for trade openness is much greater than for renewable energy consumption. The estimated results of the Dumitrescu and Hurlin (2012) test reveal bidirectional causality between green economic growth and renewable energy consumption, providing support for the feedback hypothesis.

This paper provides strong evidence of the contribution of renewable energy consumption on green economy for a wide range of countries. Despite the costs of establishing renewable energy facilities, it is evident that these facilities contribute to the green growth of an economy. Governments and public authorities should promote the consumption of renewable energy and should have a support policy to promote an active renewable energy market. Furthermore, the regulators must constitute an efficient regulatory framework to favor the renewable energy consumption.

Many countries focus on increasing their GDP without taking the environmental impacts of the growth process into account. This paper shows that renewable energy consumption points to the fact that countries can still increase their economic growth with minimal damage to environment. Despite the costs of adopting renewable energy technologies, there is still room for economic growth.

This paper provides evidence on the contribution of renewable energy consumption on green economic growth for a wide range of countries. The paper focuses on the impact of renewable energy on economic growth by taking environmental degradation into consideration on a wide scale of countries.

Traditional risk assessment (RA) methodologies cannot model vagueness in risk and cannot prioritize corrective-preventive measures (CPMs) by considering effectiveness of those on risk types (RTs). These cannot combine and reflect accurately different subjective opinions and cannot be used in a linguistic manner. Risk factors (RFs) are assumed to have the same importance and interrelations between RFs are not considered. This study aims to overcome these disadvantages by combining fuzzy logic with multi-criteria decision-making in a dynamic manner.

This study proposes a novel three-stage fuzzy risk matrix-based RA integrating fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) and fuzzy multi-attributive border approximation area comparison (F-MABAC). At the first stage, importance weights of RFs are computed by F-DEMATEL. At the second stage, risk degrees of RTs are computed via using fuzzy risk matrix. At the third stage, CPMs are ranked by F-MABAC. Finally, a numerical example for RA in a warehouse is given.

Results show that developing instructions for material loading or unloading is the most important CPM and severity is the most important RF for the warehouse.

This study has originality in terms of having fuzzy dynamic structure. At first, RFs are assumed to be criteria sets then, RTs are assumed to be criteria set considering their risk degrees to rank CPMs in a fuzzy manner. Risk degrees of RTs are used for weights of RTs and effectiveness of CPMs are used for performance values of CPMs.

This study investigates the determinants of digital competencies (DC) of students and professionals in accounting.

A total of 278 valid questionnaires were collected from 145 accounting students and 133 professionals to test the relationship between some characteristics of learners through the t-test and two-way ANOVA test.

The results showed a difference in DC between students and professionals. Whereas the characteristics of students do not influence their DC, gender and the number of short courses significantly affect their DC. Information and communication technologies (ICTs) should be provided in accounting programs as core competencies.

A sample size that is not too large and does not include learners and professionals in the central and northern areas is problematic.

The key findings support the development of policies for digital transformation in accounting.

Accounting is one of the professions that must keep up with the changes in the world, which is in the process of rapid digitalization. Hence, this study is valuable for accounting practitioners, higher education institutions and managers to enhance DC continuously.

This study aims to empirically investigate the linkages between digital trails of social signals (content and profile features of bitcoin-related tweets) and bitcoin price return using a VAR-BEKK-GARCH model.

Bitcoin-related tweets were collected every hour for six months from September 1, 2020, to February 29, 2021. The analysis involved two steps: first, examining tweet content, profiles, sentiment and emotions; and second, investigating the relationship between social signal volatility and hourly bitcoin price return.

Results indicate that bitcoin price changes can impact the sentiment expressed in tweets about bitcoin, and vice versa. While sadness exhibits a bidirectional volatility spillover with bitcoin, fear and anger display a one-period lag. Quartile analyses reveal that only fear in the second quartile shows a bidirectional spillover effect with bitcoin, while all other emotions except sadness demonstrate a unidirectional spillover effect in all remaining quartiles.

The study uses a novel two-step approach to analyze volatility spillovers between social signals and bitcoin price returns. Findings can guide investors and portfolio managers in making better allocation decisions and assist policymakers and regulators in reducing the adverse effects of bitcoin’s volatility on financial system stability.

This study aims to investigate the relationships between firms’ strategic planning (SP), leadership and technology transfer competence (TTC) by specifically incorporating the mediating role of strategic quality management (SQM).

This study performs structural equation modeling using AMOS on survey data collected from 200 Turkish firms operating in multiple industries and sectors.

This study finds that leadership in Turkish firms operating in multiple sectors is positively associated with SQM. This study further finds that SQM positively influences Turkish firms’ TTC and mediates the roles of SP and leadership in TTC.

A key research implication from this study relates to the mediating role of SQM in TTC in an emerging economy context. This study highlights that SP and leadership can play an essential role in TTC through the mediating mechanism of SQM. Consequently, SQM emerges as a crucial linking pin in conveying the impact of quality management practices on technology transfer in emerging markets.

An essential managerial implication of this study relates to the critical roles of leadership, SP and SQM in TTC. For the managers of firms operating in a relatively uncertain emerging context such as Turkey, it is essential to adopt a supportive and empowering leadership style, where open communication and innovative activities are viewed positively and SQM is adopted holistically. Also, SP should be streamlined throughout the firm and followed by SQM to support TTC.

This paper links the technology (and knowledge) management and the strategy and leadership literature streams by focusing on the mechanisms of technology transfer and delving into the linkages between SQM, leadership, SP and TTC. It specifically presents SP and leadership as precursors to SQM in their joint influence on TTC. Accordingly, this research bridges technology, strategy and leadership research and provides a broader picture of technology transfer that encompasses the joint role of different processes in firms’ TTC.

This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.