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The purpose of this paper is to discuss an online sensor-based support system which the authors believe can be useful in such scenarios. Persons with a cognitive impairment, such as those with Alzheimer’s disease, suffer from deficiencies in cognitive skills which reduce their independence; such patients can benefit from the provision of further assistance such as reminders for carrying out instrumental activities of daily living (IADLs).

The system proposed processes data from a network of sensors that have the capability of sensing user interactions and on-going IADLs in the living environment itself. A probabilistic learning model is built that computes joint probability distributions over different activities representing users’ behavioural patterns in performing activities. This probability model can underpin an intervention framework that prompts the user with the next step in the IADL when inactivity is being observed. This prompt for the next step is inferred from the conditional probability taken into consideration the IADL steps that have already been completed, in addition to contextual information relating to the time of day and the amount of time already spent on the activity. The originality of the work lies in combining partially observed sensor sequences and duration data associated with the IADLs. The prediction of the next step is then adjusted as further steps are completed and more time is spent towards the completion of the activity, thus updating the confidence that the prediction is correct. A reminder is only issued when there has been sufficient inactivity on the part of the patient and the confidence is high that the prediction is correct.

The results of this study verify that by including duration information the prediction accuracy of the model is increased and the confidence level for the next step in the IADL is also increased. As such, there is approximately a 10 per cent rise in the prediction performance in the case of single sensor activation in comparison to an alternative approach which did not consider activity durations.

Duration information to a certain extent has been widely ignored by activity recognition researchers and has received a very limited application within smart environments.

This study concludes that incorporating progressive duration information into partially observed sensor sequences of IADLs has the potential to increase performance of a reminder system for patients with a cognitive impairment, such as Alzheimer’s disease.

This paper aims to discuss an online sensor-based support system which is believed to be useful for persons with a cognitive impairment, such as those with Alzheimer’s disease, suffering from deficiencies in cognitive skills which reduce their independence. Such patients can benefit from the provision of further assistance such as reminders for carrying out instrumental activities of daily living (iADLs).

The system proposed processes data from a network of sensors that have the capability of sensing user interactions and ongoing iADLs in the living environment itself. A probabilistic learning model is built that computes joint probability distributions over different activities representing users’ behavioural patterns in performing activities. This probability model can underpin an intervention framework that prompts the user with the next step in the iADL when inactivity is being observed. This prompt for the next step is inferred from the conditional probability, taking into consideration the iADL steps that have already been completed, in addition to contextual information relating to the time of day and the amount of time already spent on the activity. The originality of the work lies in combining partially observed sensor sequences and duration data associated with the iADLs. The prediction of the next step is then adjusted as further steps are completed and more time is spent towards the completion of the activity; thus, updating the confidence that the prediction is correct. A reminder is only issued when there has been sufficient inactivity on the part of the patient and the confidence is high that the prediction is correct.

The results verify that by including duration information, the prediction accuracy of the model is increased, and the confidence level for the next step in the iADL is also increased. As such, there is approximately a 10 per cent rise in the prediction performance in the case of single-sensor activation in comparison to an alternative approach which did not consider activity durations. Thus, it is concluded that incorporating progressive duration information into partially observed sensor sequences of iADLs has the potential to increase performance of a reminder system for patients with a cognitive impairment, such as Alzheimer’s disease.

Activity duration information can be a potential feature in measuring the performance of a user and distinguishing different activities. The results verify that by including duration information, the prediction accuracy of the model is increased, and the confidence level for the next step in the activity is also increased. The use of duration information in online prediction of activities can also be associated to monitoring the deterioration in cognitive abilities and in making a decision about the level of assistance required. Such improvements have significance in building more accurate reminder systems that precisely predict activities and assist its users, thus, improving the overall support provided for living independently.

Arthritis is the most prevalent chronic condition in persons ages 65 and older and is projected to increase substantially as the population ages. The purpose of this research is to assess if age, duration of arthritis, and severity of arthritis exert independent effects on various aspects of the disability process: functional limitations, activities of daily living (ADL) limitations, and instrumental activities of daily living (IADL) limitations. Type of arthritis, socio-demographic factors, behavioral factors, and additional health statuses are also examined. Using longitudinal data from the Health and Retirement study, results show age and severity of arthritis are related to the number of functional limitations one has and to the odds of having ADL and IADL limitations. Duration of arthritis is positively related to functional limitations and to the odds of reporting ADL limitations. Duration of arthritis is not significantly related to IADL limitations, which are strongly linked to performing social roles and have less to do with physical functioning compared to ADL tasks and functional tasks. There is no difference between those with established arthritis compared to those who have had it for a shorter time period, suggesting those with arthritis adapt to social tasks better than physical tasks. The resources used to cope with IADL limitations may be more effective over time compared to those used to cope with functional limitations and ADL disability. Understanding the context of functional limitations and disability among those with arthritis may lead to improved support and care for those living with arthritis.

This paper aims to study the learning-by-exporting effect among small-to-medium-sized enterprises (SMEs). Specifically, the authors propose a dynamic perspective and suggest that learning-by-exporting is duration-dependent and contingent upon the born global internationalization strategy. In earlier phases of export activities, exporting has had a strong positive effect on SMEs’ innovations, which, however, diminishes over time. This inverted U-shape effect is even more distinct for born global firms.

The authors used longitudinal data with 1,689 Canadian SMEs to test their hypotheses. A two-stage instrumental approach is used to take into account the endogeneity of the born global international strategy on new product innovations.

Born globals learn faster at the early stages of exporting but also restrain their innovations more strongly than gradual internationalizers in the longer run, leveling out the initial learning advantages of newness. Thus, this study suggests that born globals have a significantly different learning trajectory than gradual internationalizers.

To maximize the benefits of exporting on innovation, managers should focus on learning during the initial years of exporting. However, once this period has passed, it is advisable for managers to invest in research and development as well as other innovation activities to complement the learning effect of exporting. Born global firms experience more rapid learning at the initial stage of exporting, but such learning effects wear off quicker later than gradually internationalized firms. For SME managers, this study helps draw their attention to the learning benefits of exporting in the initial years of export participation.

This study corroborates recent studies arguing for a “learning-by-exporting” effect. Providing longitudinal firm-level evidence, the authors also forward a dynamic perspective and show that learning by exporting is duration dependent and contingent upon the market entry strategy pursued by SMEs.

To deal with the agenda of extensive research to establish employer branding as a valuable Human Resource (HR) practice, this study aims to examine perception of seafarer to explore the attributes related with employer branding in maritime industry. This study intends to explore the applicability of instrumental-symbolic framework of employer branding in maritime industry to understand the dimensions related with attractiveness of seafarers’ jobs.

Sample of the study is Indian seafarers include only officers from both deck and engine. Total 276 usable responses were considered at the end for data analysis.

Both, the instrumental and symbolic attributes explained significant variance in predicting attractiveness of seafarers’ occupation, thus supporting hypotheses 1 and 2. In particular, among instrumental dimensions, social/team activities, structure, advancement, travel opportunities and pay and benefits positively predicted seafarers’ attraction towards their job. As symbolic dimension, sincerity, competence and prestige was positively related, and ruggedness was negatively related to attractiveness of the present job among seafarers.

Overall, the present findings ascertain the utility of the framework as a conceptualization of employer brands and support the applicability of instrumental-symbolic framework for understanding the dimensions of occupational attractiveness in different context and culture, i.e. Indian Seafarers.

Although the popularity of employer branding is growing amongst human resources practitioners, but still, there is dearth of academic (mainly empirical research) literature on the subject, `appeals to management researchers (Cable and Turban, 2001; Backhaus and Tikoo, 2004, Edwards, 2009; alniacik and alniacik, 2012; Kucherov and Zavyalova, 2012). With this in consideration and to deal with the agenda of extensive research to establish employer branding as a valuable HR practice, the present study examines perception of seafarer to explore the attributes related with employer branding in maritime industry.

Based on the institutional background of mandatory requirement of performance-based executive equity incentives, this paper aims to investigate the impacts of executive equity incentives, vesting periods and vesting performance conditions on corporate innovation.

The empirical analysis is based on the detailed data of equity incentives in China’s listed companies from 2006 to 2014, the Tobit method is implemented to estimate the regression coefficients, and the instrumental variable (IV) approach, Heckman two stage regression, propensity score matching and difference-in-difference models are adopted to solve the problem of endogeneity in several robust tests.

This paper documents that equity incentives and vesting periods are significantly and positively related to corporate innovation measured by R&D investment and patent applications, yet requirements on vesting performance impede corporate innovative activities. Specifically, compared with non-equity incentive companies, the R&D investment and the number of patent applications of equity incentive companies are 40 and 46.2 per cent higher, respectively. A one year increase in equity incentive duration can correspondingly increase the R&D investment by 15 per cent and the patent applications by 18.3 per cent. However, a one standard deviation increase in industry-adjusted ROE target reduces corporate R&D investment by 5 per cent and the patent applications by 8.39 per cent. The main empirical findings still hold after several robust tests.

This paper confirms that the impact of performance-based compensation system on corporate innovation depends on its structure. Specifically, the empirical findings suggest that equity incentive plans being correctly designed can enhance corporate innovative activities, but myopic managers will damage the corporate innovation.

This paper investigates the influence of equity incentive structure on equity incentive effect based on the institutional background of mandatory requirement of performance-based executive equity incentives. It provides an opportunity to understand the mystery of equity incentives, which helps to enrich the structure of equity incentive theoretically. The empirical evidence confirms the importance of tolerating short-term failure and extending the horizon of managerial decision-making on promoting innovation. Overall, the research indicates that only well-designed equity incentive plans can promote innovation, which contributes to regulators and practitioners to form a rational understanding of the premise of equity incentives in promoting innovation and provides a reference for their decision-making.

Previous research regarding shaping factors and major causes behind accidents in the construction field is reviewed. In particular, a hypothetical model is established to correlate activity time, cost and safety in the context of construction activity acceleration planning. Two demonstration cases are presented to illustrate the proposed theoretical model in the context of critical activity expedition planning. Further, a third case uses a 100-activity project to perform the global level total project time and cost analysis, identifying specific activity acceleration plans that would materialize the shortened total project time at the lowest total project cost.

This research proposes a safety-centric application framework to guide construction acceleration planning at both activity and project levels while taking sufficient preventive measures against safety hazards and accidents. As planning construction acceleration by factoring in safety constraints inevitably drives up cost, it is imperative to control increases in activity costs at the local level in connection with schedule acceleration planning while at the same time not compromising on safety. This research also addresses this critical question through performing global level total project time and cost analysis.

An application framework is proposed for guiding a planner through identifying accident shaping factors, obeying schedule acceleration rules and accounting for safety-related costs in attempts to mitigate hazardous situations on-site at both activity level (local) and project level (global), resulting in (1) minimizing the increase of total project cost in schedule acceleration while at the same time not compromising on safety at individual activities; (2) producing specific execution plans on each individual activity in terms of the amount of time to crash and the associated activity cost.

This study is original in developing theories and methods for evaluating the impact of safety constraints upon construction time and cost in activity acceleration planning and project time-cost analysis. The research fills a gap in knowledge in terms of how to factor in sufficient safety constraints while achieving project time and cost objectives on construction acceleration planning at both activity and project levels.

The purpose of this paper is to examine the determinants of a household's social capital in the form of community group participation and empirically analyses the roles that social capital plays in helping rural households rebuild productive assets after shocks.

In this paper, social capital is modelled as a household's intensity of group participation measured by the density and active participation in group activities as well as their multiplicative and additive indices. Instrumental variable methods were used to address the problem of endogeneity associated with social capital.

The results indicate that household characteristics such as age, education level, dependence ratio and years of village residence as well as village-level characteristics such as the village population density are critical determinants of social capital. In addition, social capital measured in form of density of participation in group activities and attendance score as well as multiplicative and additive indices of these have significant positive effects on the household ability to rebuild livestock assets.

The authors realize that several weakness in the approach could compromise the validity of the findings. These weaknesses include: the cross-sectional nature of the data, the omitted variable bias, the endogeneity concerns of social capital and the identification strategy, sample size and the dimensions the authors chose to measure social capital. Future research should explore the factors that can help households to engage more in-group activities.

The findings have important implications for government policy especially in areas of agricultural development and poverty reduction. Specifically, governments should pay close attention to the various social groups as they can serve as important channels to achieve better social economic outcomes, including the accumulation of rural assets, as is the case with livestock assets in rural Uganda.

Many governments in Sub-Saharan Africa are constrained to provide basic public goods to the people. This is due to a combination of limited budgets and lack of good leadership. In such circumstances, the people have to rely on their collective/social effort to take advantage of market opportunities. Such opportunities can be accessed using the existing social structures whose norms and the trust between members permit cooperation.

The study contributes to a small but growing empirical literature on social groups and how they can mediate social economic outcomes especially for rural households. The empirical estimations take into consideration the endogeneity concerns associated with social network capital. The paper will be useful for policy makers and researchers who may have a keen interest in the roles that group activities play in agricultural development and poverty reduction.

This paper aims to estimate the impact of job search on the internet on the probability of re‐employment and the duration of unemployment spells.

The study uses national panel datasets from Germany (SOEP 2003‐2007) and South Korea (KLIPS 1996‐2006) to estimate probit and Hausman‐Taylor IV models of the impact of job search on the internet on the probability of re‐employment. The study also explores duration analysis with the aim of estimating the impact of internet job search on the duration of unemployment.

In Germany and South Korea job seekers who used the internet had a 7.1 and 12.7 percentage point higher probability, respectively, of being re‐employed in the next 12 months. Furthermore, job seekers who used the internet had a shorter duration of unemployment in both Germany and South Korea.

Over the past decade, internet penetration rates and use of the internet in job search have risen sharply across the world. The internet has significantly changed the job application process and improved the channels of communication between employers and job seekers. The findings of the research indicate that the internet is beneficial and should be a part of job search efforts.

The contribution of this study is twofold. It is the first study to use panel datasets to analyze the link between internet use and job search outcomes. Therefore, the results are robust to unobserved heterogeneity problems. The study also addresses the issue of endogeneity of job search on the internet by using the Hausman‐Taylor IV model.