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The activity of scholars presupposes models of the universe, i.e. structures, which can be used to simulate and anticipate the evolution of phenomena. Such models are usually conceived with the purpose of answering certain peculiar problems, specific to a well‐defined field. As a result, believes that this kind of research does not explain the universe as such, or the world at large, whereas the various scientific models tell us something about the world of scholars, and about how they approach the universe.

The purpose of the paper is to present three different contributions to a general model theory which the authors think as relevant to systems research based on systems theory, cybernetics and constructivism. This also implies that the three contributions are shown to be of use both in the study of systems that operate by models, as well as in the practice of designing models.

The text is conceptual and mainly of a descriptive and referring character. Besides the sections on the three contributions to a model theory, the authors have inserted sections that relate them to systems theory. This is also achieved by the help of some simple models.

The paper also points to models as important instruments in constructing and selecting information to observing systems, and the authors hope that the text can be helpful in developing better knowledge of how models work.

The text is about observing systems that observe by models, and that is probably a somewhat new perspective. It is hoped that the paper can be inspiring to further studies on this matter.

This paper aims to develop generic strategies for improving energy consumption for location sensing on smartphones and compares the results of iOS and Android implementations. Mobile smartphone applications utilizing localization sensors (e.g. Global Positioning System) collectively face the problem of battery draining. Energy consumption is at a peak when applications permanently and stolidly use those sensors, even if their excessive exploitation is avoidable (e.g. when the user carrying the device is not moving).

Considering contextual parameters affecting localization of mobile devices (i.e. incorporating movement probability, speed, etc.) is the basic idea for developing a strategy capable of reducing energy consumption for location determination on mobile devices. This paper explains the paradigm and draws the architecture for a generic context-based energy saving strategy for mobile location-based services.

The paper reveals the positive implications in terms of energy consumption measured in the course of exhaustive tests for iOS and Android devices and discusses accuracy issues and potential workarounds, especially focusing on Apple’s M7 motion co-processor for consuming accelerometer data on a low energy level.

The paper identifies and measures energy issues for location determination on smartphones and presents a generic and heuristic concept for saving energy.

Detecting and tracking the position of a mobile user has become one of the important subjects in many mobile applications. Such applications use location based services (LBS) for learning and training user movements in different places (cities, markets, airports, stations) along different modes of transport (bus, car, cycle, walk). To date, GPS is the key solution to all LBS but repeated GPS querying is not economical in terms of the battery life of the mobile phone. The purpose of this paper is to study how cheap and energy‐efficient air pressure sensors measuring the altitude could be used, as a complement to the dominant GPS system. The location detection and route tracking task is then accomplished by matching the collected altitude traces with the altitude curves of stored data to find the best matching routes.

The cornerstone of the authors' approach is that a huge amount of route data, collected with GPS devices, is available in various cloud services. In order to evaluate the mechanism of matching routes with altitude data, the authors build a prototype system of crowd‐sourced database containing only altitude data of different routes along different modes of transport. How accurately this stored altitude data could be matched with the collected altitude traces is the key question of this study.

Results show that, within a certain level of accuracy, older repeated routes can be detected from newly tracked altitude traces. Further, the level of accuracy varies depending on the length of path traversed, route curvature, speed of travel and sensor used for tracking.

The new contribution in this paper is to propose an alternative route detection mechanism which minimizes the use of GPS query. This concept will help in retrieving the GPS coordinates of already traversed routes stored in a large database by matching them with currently tracked altitude curves.

Based on the social exchange theory, the aim of the present study is to examine the effects, both direct and indirect (through sustainability-oriented innovative behaviors [SIBs]), of sustainable project leadership (SPL) on sustainable project performance (SPP). Project management approaches (PMAs) (traditional, hybrid and agile) were examined as conditional factors in the “SPL–SIBs” relationship.

The study employs structural equation modeling based on data collected from 197 software engineering project team members working in the financial industry in Poland.

The study revealed that SPL significantly, positively affected SPP. It also provided evidence for the significant mediating impact of SIBs in the relationship between SPL and SPP and the conditional effect of agile and hybrid PMAs on the “SPL–SIBs” relationship.

The novelty of this work lies in introducing sustainable leadership into project management research, proposing and testing a unique and complex research framework, designing valid scales for measuring SPL and SPP, and suggesting many theoretical and empirical implications.

This paper aims to propose a gesture recognition method at an early stage. An accelerometer is installed in most current mobile phones, such as iPhones, Android-powered devices and video game controllers for the Wii or PS3, which enables easy and intuitive operations. Therefore, many gesture-based user interfaces that use accelerometers are expected to appear in the future. Gesture recognition systems with an accelerometer generally have to construct models with user’s gesture data before use and recognize unknown gestures by comparing them with the models. Because the recognition process generally starts after the gesture has finished, the output of the recognition result and feedback delay, which may cause users to retry gestures, degrades the interface usability.

The simplest way to achieve early recognition is to start it at a fixed time after a gesture starts. However, the degree of accuracy would decrease if a gesture in an early stage was similar to the others. Moreover, the timing of a recognition has to be capped by the length of the shortest gesture, which may be too early for longer gestures. On the other hand, retreated recognition timing will exceed the length of the shorter gestures. In addition, a proper length of training data has to be found, as the full length of training data does not fit the input data until halfway. To recognize gestures in an early stage, proper recognition timing and a proper length of training data have to be decided. This paper proposes a gesture recognition method used in the early stages that sequentially calculates the distance between the input and training data. The proposed method outputs the recognition result when one candidate has a stronger likelihood of recognition than the other candidates so that similar incorrect gestures are not output.

The proposed method was experimentally evaluated on 27 kinds of gestures and it was confirmed that the recognition process finished 1,000 msec before the end of the gestures on average without deteriorating the level of accuracy. Gestures were recognized in an early stage of motion, which would lead to an improvement in the interface usability and a reduction in the number of incorrect operations such as retried gestures. Moreover, a gesture-based photo viewer was implemented as a useful application of our proposed method, the proposed early gesture recognition system was used in a live unscripted performance and its effectiveness is ensured.

Gesture recognition methods with accelerometers generally learn a given user’s gesture data before using the system, then recognizes any unknown gestures by comparing them with the training data. The recognition process starts after a gesture has finished, and therefore, any interaction or feedback depending on the recognition result is delayed. For example, an image on a smartphone screen rotates a few seconds after the device has been tilted, which may cause the user to retry tilting the smartphone even if the first one was correctly recognized. Although many studies on gesture recognition using accelerometers have been done, to the best of the authors’ knowledge, none of these studies has taken the potential delays in output into consideration.

The study aims to examine the connection between practices of total quality management (TQM) and sustainability in Malaysia food and beverages companies (FBC). Continuous process improvement, benchmarking, management leadership, human resources management, quality assurance, service design and information and analysis as TQM practices are considered and their relationship, respectively, with sustainable performance.

A survey questionnaire is administered to gather responses from 303 FBC, while 98 responses are useable and subsequently analysed using partial least squares structural equation modelling.

The results reveal that effective implementation of continuous process improvement, benchmarking, quality assurance, service design and information and analysis have positive and significant effect on sustainability.

The scope of the present study was limited to FBC in Malaysia, and a cross-sectional design was employed to examine the hypothesized relationships at a single point in time.

The proposed and developed model of this study can be employed by policy and decision makers in the industry. This model can be considered by practitioners in the industry to implement critical policies in the future.

The premises of the institutional and contingency theory are supported by re-affirming the importance of contingencies and institutions for any successful strategic practices to enhance sustainable performance by implementing TQM.

In a highly competitive and globalised era, agile organisations proactively steer towards sustainability. This situation persuaded the organisations to align Quality Management (QM) initiatives to achieve sustainable outcomes. This study aims to explore quality–sustainability linkage, explicitly focusing on attaining the prestigious IAQ Quality Sustainability Award. Further it investigates, the impact of QM as a strategy for promoting sustainability to meet sustainable development goals (SDGs).

Due to the lack of substantial literature connecting QM to sustainability, the current research adopted an explanatory multiple-case study. Six cases were purposively chosen for the study. Three cases of those who have achieved the prestigious IAQ Quality Sustainability Award and remaining have been selected that have fallen short of receiving the award. A detailed within-case and cross-case examinations involving six cases that reported their QM achievements aligned with SDGs.

The findings demonstrate the significant role of QM adoption in achieving positive results from the perspective of SDGs, such as reduced environmental impacts, improved operational efficiency and enhanced quality of life. Effective stakeholder collaboration, proficiency in analytical tools and strategic alignment with SDGs emerged as critical success factors. Conversely, weak linkage with sustainability and unclear approaches were crucial challenges in attaining the IAQ Quality Sustainability Award.

This paper outlines essential commandments for organisations actively seeking to promote sustainability. It offers valuable insights for decision-makers, facilitating a profound understanding of the challenges and opportunities in pursuing sustainable performance.

The distinctive nature of this study lies in its dedicated exploration of the intricate relationship between QM deployment and its true impact on the achievement of the SDGs.