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Through the lens of self-determination theory (SDT), the purpose of this paper is to examine the influence of autonomous and controlled motivational regulations in driving consumer participation in social brand engagement (SBE) practices. In addition, the moderating effects of cognitive effort and consumer demographic variables (age and gender) are examined.

The proposed model is tested by employing a quantitative survey design consisting of 832 consumers with prior experience in engaging with brands on social media. The respondents were conveniently interviewed using online questionnaire. The model estimation was done through structural equation modelling with AMOS 23.0.

The findings indicate that intrinsic, integrated, introjected and external motivational regulations significantly influence consumer participation in SBE activities, whereas identified regulation does not. Furthermore, while age and gender presented mixed interaction effects on the paths examined, cognitive effort does not moderate the influence of autonomous and controlled motivational regulations on SBE participation.

This study employed a cross-sectional survey to explore consumer motivation and cognitive effort in SBE practices. As an exploratory study, the findings may be limited and not conclusive, which could limit the generalisation of the results reported.

This study demonstrates a need for retailing managers to understand customers’ varying intentions or needs in participating in online SBE activities As a result, retail managers need to adopt social media strategies that could elicit interest and curiosity on the part of the customer to excite them to participate in the brand social interactions.

This research contributes to the conceptual understanding of SBE through the application of SDT, and contends that cognitive effort does not moderate consumer participation in SBE practices. Also, the mixed findings resulting from the moderation test of age and gender sheds light on specific types of regulated motivations that are either moderated or not in relation to these demographic variables.

A cell phone that behaves in a manner reflective of the current context has been a goal for the pervasive and ubiquitous research communities for a long time. This paper aims to demonstrate how two aspects of context – location and activity – can be inferred using GSM data present on standard cell phones.

A background knowledge of GSM networks is provided, followed by an assessment of the stability of signal strength levels in order to establish their usefulness in inferring aspects of context. A qualitative location system using GSM signals is presented and how to infer the current activity of the cell phone carrier is demonstrated.

The paper shows that by using the patterns of signal strength fluctuations and changes to the current serving cell and monitored neighbouring cells it is possible to distinguish between various states of movement such as walking, driving a car and remaining stationary.

The paper focuses on the practical aspects of deploying and managing location based services in dynamic outdoor environments.

Proposes a heuristic iterative scheduling algorithm for the resource constrained project scheduling problem. Considers a general model where activities are represented by multiple operating modes and each operating mode is constituted of different activity durations and resource requirements. The performance measures considered are the minimization of project duration and the maximization of net present value (NPV). In the cash flow model assumed, activity expenditures take place at their start times and the project payment is made on its completion. The iterative scheduling algorithm consists of forward/ backward scheduling passes, where consecutive scheduling passes are linked by updated activity time windows. The iterative algorithm is supported by a conflict‐based activity selection technique called local constraint based analysis (LCBA). A considerable amount of improvement in both performance criteria is observed when the results of the iterative algorithm are compared with the results given by the initial forward schedule.

The purpose of this paper is to compare the effect of different representations while teaching basic algorithmic concepts to novice programmers.

A learning activity was designed and mediated with two conceptually different learning environments, each one used by a different group. The first group used the learning environment “Visual Flowchart”, which enables the students to construct and examine an algorithm using visual representation based on actual flowchart objects. The second group used the software “Language Interpreter”, which allows the students to express an algorithms using pseudocode.

Analysis of results among the two groups showed no statistically significant differences in the students’ performance with respect to the tool they used to solve the activity, the school stream they followed in high school and their gender.

The lack of difference among the two groups could be attributed to the non‐complicated nature of the given activity. In addition, longitudinal studies of the effect of the different representation in the frame of an introductory first semester academic course in computer science could further validate the results.

Two alternative learning environments aimed to support learning of basic programming skills.

Two alternative learning environments were presented and discussed in detail, aimed to support learning of basic programming skills. The conclusions of the present study are in contrast to the research that has taken place in the past which compared usage of flowcharts and pseudocode to educate novice programmers, and wider adoption of “flowcharts” was depicted.

Physical inactivity has a considerable negative impact on health. Physical activity has reduced partly due to workplace and lifestyle changes, causing people to spend more time in buildings and increasing sedentary behaviour. The purpose of this paper is to address a largely untapped opportunity for designers and managers to improve building users’ health by designing buildings that raise users’ Non-Exercise Activity Thermogenesis (NEAT) levels. In this research a conceptual model was developed to assess buildings’ performance in providing NEAT-promoting opportunities through building design features and management, in relation to building users’ propensity for NEAT behaviours.

The conceptual model was developed by a multi-disciplinary team of researchers and data to populate the model was obtained through a survey of 75 buildings in Jakarta (Indonesia).

The presented proof-of-concept shows that the model’s “meso-scale” approach to study physical activity and building design can lead to potential improvements of NEAT levels and physical activity in buildings.

The review of precedent models shows that this subject has been researched at micro-scale (i.e. detailed monitoring of individuals’ movement) and macro-scale (i.e. epidemiological studies of populations’ health). The presented model is original, as it explores a “meso-scale”(i.e. building scale) that is unique.

Discussion regarding systems that promote innovation, aptly named innovation ecosystems, has been intensifying both in academia and business. The purpose of this paper is to introduce the activity theory as a theoretical framework for conceptualising and studying innovation ecosystems. Using the activity theory, it investigates elements that affect the success and viability of innovation ecosystems formed between startups and incumbent firms, collaborating with an established firm within the context of an open innovation programme.

This study uses an exploratory case research approach and proposes the activity theory as a theoretical background to be used in innovation ecosystem research. Based on this approach, this study draws from interviews and research observations in an innovation ecosystem formed between an established firm and various startups that aim to co-develop innovative offerings.

By applying the activity theory tools, this study identifies several contradictions between interacting actors of this innovation ecosystem that can adversely affect the innovation process. Furthermore, it proposes the use of the activity theory as a fitting theoretical lens to study innovation ecosystems.

The novelty of this study is related to the focus on the incumbent–startup context for extending the innovation ecosystem literature. Using the activity theory as a viable methodological tool allows us to conceptualise firms as social constructs and hence pinpoint inner characteristics that can affect and shape their interactions and the broader ecosystem. This process is further enhanced by the use of primary data that give unique insights into the inner workings of innovation ecosystems by identifying underlying contradictions.

Strategy research has long understood that reconfiguration of the scope of the activities a firm engages in over time is critical to its long-run success, while under-emphasizing differences in redeployment strategy that underlie apparently similar scope and changes in scope. In this paper, we build on the idea that a firm’s number of activities (scope) and change in activities (turnover) arise from two fundamental rates of redeployment: the rate at which activities are added and the rate at which activities are subtracted. In net, the turnover rate reflects how actively a firm reconfigures its resource base by redeploying resources via addition and subtraction of activities. We develop a model that links addition and subtraction with the composition of a firm’s activities and then provide an empirical illustration using data from the U.S. Patents and Trademarks Office. As an example of one extension, the model can be generalized to incorporate elements of absorptive capacity. The analysis contributes to our understanding of how firms reconfigure their activities and provide managers with a clearer understanding of tools that guide redeployment of existing resources.

One often thinks of competition as a mechanism whereby undertakings are forced to answer more efficiently the needs of clients. One may wonder whether that system could be used to organize the institutional environment. Competition already exists among states or regions, where it affects their capacity to attract investment or skilled workers. Could we go further and organise institutional competition among authorities within the same territory? Electronic communications provide a good case study, with the same competencies being attributed to regulators, competition authorities and judicial power.

The purpose of this paper is to consider one of the recent and practical extensions of the resource-constrained project scheduling problem (RCPSP) termed as the multi-skill resource-constrained project scheduling problem (MSRCPSP) for investigation. The objective is the minimization of the makespan or total project duration.

To solve this complex problem, the authors propose a teaching–learning-based optimization (TLBO) algorithm in which self-study and examination have been used as additional features to enhance its exploration and exploitation capabilities. An activity list-based encoding scheme has been modified to include the resource assignment information because of the multi-skill nature of the algorithm. In addition, a genetic algorithm (GA) is also developed in this work for the purpose of comparisons. The computational experiments are performed on 216 test instances with varying complexity and characteristics generated for the purpose.

The results obtained after computations show that the TLBO has performed significantly better than GA in terms of average percentage deviation from the critical path-based lower bound for different combinations of three parameters, namely, skill factor, network complexity and modified resource strength.

The modified TLBO proposed in this paper can be conveniently applied to any product or service organization wherein human resources are involved in executing project activities.

The developed model can suitably handle resource allocation problems faced in real-life large-sized projects usually administered in software development companies, consultancy firms, R&D-based organizations, maintenance firms, big construction houses, etc. wherein human resources are involved.

The current work aims to propose an effective metaheuristic for a more realistic version of MSRCPSP, in which resource requirements of activities may be more than one. Moreover, to enhance the exploration and exploitation capabilities of the original TLBO, the authors use two additional concepts, namely, self-study and examination in the search process.

In good or bad times, training plays an important part in the development of knowledge and skill in all sectors of the economies around the world. Just as the successful sportsperson must train to keep on winning, so too must any organisation. Whilst the effectiveness of the sportsperson's coach is reflected by success in winning events, it is often more difficult to evaluate the success or effectiveness of the organisational trainer. Many other factors come into play in determining individual and organisational performance — methods of work used; efficient supply of materials; adequate equipment; attitudes of senior management, and of customers; the whims of the market place, government policy and the world economic situation. With so many variables involved it may seem futile to bother to study effectiveness.