Search results

The purpose of this paper is to identify demographic differences based on how users interact with web applications. The research is needed to develop future systems able to adapt the representation of online information to the user’s specific needs and preferences improving its usability. The following question guides this quest: is there a direct relationship between age and/or gender and interaction?

GOMS (goals, operators, methods, and selection rules) analysis was used to reduce complex interaction tasks into basic operators like pointing, dragging, typing, etc. An experiment was designed to analyse the user performance in the use of these operators through five complex tasks: point-and-click, drag-and-drop, text selection, text edition and menu selection. The sample comprises 592 individuals which took part in the experiment. The performance was analysed using multivariate regression analysis. User laterality and the the user experience were used as control variables.

The factors studied are significant enough to support user classification. The analysis evidenced that men performed significantly better than women when executing interaction pointing and dragging GOMS’s operators, but no significant differences arose with regard to the performance in the typing operators. Older users performed worse in all the interaction tasks. No significant performance differences were detected between left and right-handed users.

The study pretends to lay the ground for developing artificial intelligence-based classification systems (e.g. neural networks, decision trees, etc.) able to detect significant differences in user performance, classifying users according to their age, gender and laterality.

This user profiling would drive the organisation, selection and representation of the online information according to the specific preferences and needs of each user. This would allow the design of new personalisation algorithms able to perform dynamic adaptation of user interfaces in order to improve the usability of online information systems.

This work extends previous research on user performance under a new approach and improved accuracy. First, it relies on the combined and simultaneous analysis of ageing and gender and the use of user laterality and experience as control variables. Second, the use of the GOMS analysis allowed the design of tests that closely resemble the user interaction in online information systems. Third, the size of the sample used in this analysis is much bigger than those used in previous works, allowing a more thorough data analysis which includes the estimation of an advanced model which is quantile regression.

The purpose of this paper is to look into production competence theory by proposing and validating a multidimensional construct, and offering additional empirical evidence regarding the contribution of production competence to business performance.

Production competence is defined as a second‐order factor/construct in terms of five underlying dimensions: cost, flexibility, quality, delivery and environmental protection competence. Different scales are used to measure the construct, validated by a multi‐step process. Data from 274 manufacturing firms and structural equation modelling as the main technique are used for the analysis.

The paper suggests that manufacturing capabilities and their alignment with the competitive priorities pursued must be considered to explain the contribution of manufacturing to business performance. The provided evidence suggests that the manufacturing function significantly contributes to business performance, and enables us to conclude that production competence is a determinant of business performance.

Firms should focus on the development of manufacturing capabilities that are key for the market (and consistent with the business strategy). To achieve this, the production function should be integrated into the strategic planning process of the overall business strategy.

Most research works to date deal with production competence as a one‐dimensional construct and reduce its measurement to a single index, fussing variables of different types. This paper provides a valid multidimensional operationalisation of production competence, considering environmental protection as a fifth manufacturing objective. It also offers additional empirical evidence regarding the positive link between production competence and business performance.

Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance.

Different types of forecasting models and their adaptation to the special circumstances of social media are analyzed and the most representative research conducted up to date is surveyed. Presentations of current research on techniques, methods, and empirical studies aimed at the prediction of future or current events from social media data are provided.

A taxonomy of prediction models is introduced, along with their relative advantages and the particular scenarios where they have been applied to. The main areas of prediction that have attracted research so far are described, and the main contributions made by the papers in this special issue are summarized. Finally, it is argued that statistical models seem to be the most fruitful approach to apply to make predictions from social media data.

This special issue raises important questions to be addressed in the field of social media-based prediction and forecasting, fills some gaps in current research, and outlines future lines of work.

This study examines the effect of design quality (i.e. appearance, navigation, information and interactivity) on cognitive and affective involvement leading to continued intention to use the online learning application.

We assume that design quality potentially contributes to enhance the individual's involvement and excitement. An experimental prototype is developed for collecting data used to verify and validate the proposed research model and hypotheses. A partial-least-squares approach is used to analyze the data collected from the participants (n = 662).

Communication, aesthetic and information quality revealed to be strong determinants of both cognitive and affective involvement. However, font quality and user control positively influence cognitive involvement, while navigation quality and responsiveness were observed as significant indicators of affective involvement. Lastly, cognitive and affective involvement equally contribute to determining the continued intention to use.

This study will draw the attention of designers and practitioners towards the perception of users for providing appropriate and engaging learning resources.

Prevalent research in the online context is focused primarily on cognitive and utilization behavior. However, these works overlook the implication of design quality on cognitive and affective involvement.

Despite the fact that agile manufacturing has been frequently promoted as a means of improving business competitiveness, little empirical evidence exists in the literature validating its positive link with business performance. The purpose of this research paper is to analyse agile manufacturing in Spain and study whether it is a critical factor for success in different industries.

A conceptual model is drawn up, based on the literature and a previous case study, to relate turbulence in the environment with agile manufacturing practices and business performance. The model is tested on a large sample of Spanish manufacturers using a survey methodology to obtain information and a structural equation model to analyse the data.

The results obtained show that, in turbulent environments, the integrated use of agile manufacturing practices promotes manufacturing competitive strength, leading to better operational, market and financial performance.

This study has two main limitations. First, it is difficult to determine the most suitable unit of analysis when studying agile manufacturing. Second, single respondent bias may be considered a limitation.

Managers should consider the integrated implementation of agile manufacturing practices in order to develop manufacturing strength and to outperform competitors in turbulent business environments.

This study adopts a systematic approach to the analysis of agile manufacturing, considering various agility practices or enablers in an integrated way and relating them not only to environmental characteristics but also to business performance. This approach is especially interesting because most of the literature on agile manufacturing deals with agility strategies or techniques in an isolated way. The study also tests the suitability of agile manufacturing in real organisations – for the first time in the Spanish context.

As social media are essentially different from traditional media, due to their social networking structures and egalitarian nature, conventional media metrics are not appropriate. Social media networks have nevertheless become another communications channel that companies use to achieve their marketing goals. Even though the measurement of marketing constructs in social media is elusive, a comprehensive means of measuring engagement is proposed for a successful social media site: Twitter. The paper aims to discuss this issue.

A measurement for customer engagement based on conceptual reflections is presented in the context of Twitter.

A new environment fostered by internet obliges companies to manage social media accounts and to assess engagement with company brands. To do so, companies need to analyze engagement trends by means of a metric, helping them to design an appropriate engagement strategy. The proposed metric provides much needed insight for companies to fine-tune their engagement strategy. Moreover, a means of calculating engagement from the parameters that Twitter makes available to the public is also proposed.

The metric for engagement in Twitter that is proposed in this paper will be the starting point for future improvements through a conceptual and empirical discussion on this issue.

This is the first proposal specifically designed for Twitter, to the best of the authors’ knowledge, for measuring engagement.

One of the main Common Core Requirements focuses on student use of authentic subject area skills. These skills are those used by professionals in the academic field of study. It is important that students develop and use appropriate historical thinking skills in the classroom. Historical skills include ability to read, write, speak, listen, and complete research based projects, and to appropriately analyze primary and secondary documents to make conclusions about what has occurred during a historical event. The implementation of instructional techniques requiring students to think like a historian are widely supported in the literature and are largely focused on the development of student historical literacy. This article examines how combining the use of children’s literature and primary sources can be used to construct a lesson promoting historical inquiry in the secondary classroom.

This paper seeks to present a scientometric analysis of the Proceedings of the McMaster World Congress on the Management of Intellectual Capital and Innovation for the 1996‐2008 period in order to better understand the evolution and identity of the discipline.

Qualitative and quantitative data analysis techniques were applied to determine author distribution, country, individual and institutional‐level productivity rankings, and employed methodologies.

It was found that an average manuscript was written by 1.73 authors. The USA, Canada and the UK were the three most productive countries, which is consistent with prior KM/IC productivity research. Most productive institutions were the University of Calgary (Canada), Polytechnic University of Catalonia (Spain) and Universidad de Oviedo (Spain). The most productive individuals were James Falconer, Jose Maria Viedma Marti and Scott Erickson. Lotka's α, which represents the degree of conference delegate retention rate, was established as 2.7. Case studies were the most frequent method of inquiry, followed by framework development and literature reviews. Surveys and usage of secondary data were the leading empirical methodologies. Interviews, laboratory experiments, and field studies were under‐represented.

The findings offer valuable insights into the state and development of the KM/IC discipline and shed some light on its identity.

Scientometric analyses are of primary interest for academic researchers and therefore the practical implications of this study are limited.

The research reported is among the first to investigate the issue of the KM/IC discipline identity from a descriptive perspective.

The problem of capacity management is one of the most difficult to tackle in business management; a situation which is aggravated in the majority of services, due to uncertain demand and personalized requirements, which make it difficult to plan and assign productive capacity. While overstaffing implies extra costs, insufficient capacity implies a lower level of attention to customer needs and therefore a lack of perceived quality. The present article tackles this problem, presenting a model that enables minimum staffing to be easily determined. By taking into account historical staffing data associated with quality data, minimum recommended workload is calculated as a function of the theoretical staff needed according to standard time. The model has been applied in two real cases.