The contribution of vacations to quality of life

The contribution of vacations to people’s life satisfaction and Quality of Life (QOL) has recently attracted substantial attention among tourism researchers. Yet, most QOL scales do not include vacations: 7% explicitly measure vacations whereas 42% only include items relating to vacations within the broader Leisure domain. Leisure and vacations, however, differ substantially in nature with leisure referring to regular home-based activities and vacations being infrequent leisure activities away from home. As a consequence of the common amalgamation of vacations with leisure, there is limited knowledge about the specific contribution of vacations to people’s QOL. The present study (1) presents empirical evidence for the contribution of vacations to QOL, (2) determines the extent of this contribution, and (3) investigates variation in the extent to which vacations contribute to the QOL of different people. Results indicate that vacations contribute to the QOL of the majority of people, are as important a QOL domain as Leisure and People, and that QOL means different things to different people at different points in their life, representing an individual and dynamic concept.     

A preliminary study on customer expectations of hotel hospitality: Influences of personal and hotel factors

This study attempts to explain the influence of personal and hotel factors on the expectation level of hotel hospitality as well as to propose a scale to measure commercial hospitality for hotel services. A total of 101 local and international hotel guests were involved in the study. The results revealed that the expectations of hotel hospitality are influenced by personal factors such as gender, purpose of stay, nationality, and private domain of hospitality. The hotel's star rating is the only hotel factor that might have strong association with hotel hospitality.     

Complexity in valuation practice: an inquiry into valuers’ perceptions of task complexity in the Dutch real estate market

The aim of this paper is to examine valuer judgement behaviour, by exploring the manifestation of task complexity in Dutch commercial valuation practice. For this purpose, we adopted a grounded theory approach and undertook 18 in-depth interviews with senior valuation professionals across the Netherlands. Our findings indicate a strong presence of situational task complexity in commercial valuation practice, as professionals operating in large valuation teams perceive different elements of task complexity throughout commercial valuation practice in comparison to peers working in small valuation teams or self-employed valuers. Further, coping strategies used to deal with task complexity vary substantially by type of valuer as well. From our data, we deducted three types of task environment constructs in which valuers operate, which basically represent the various levels of professional standards required by clients as well as organisational settings composed to meet client standards. As such, we found that task environment settings strongly coincide with perceptions of task complexity. The presence of situational task complexity in commercial real estate valuation practice points to the need for customisation of professional valuer’s development programs to facilitate valuers to deal with task complexity in different stages of valuation practice and hence contribute to advancing valuer judgement skills.     

A review of experience curve analyses for energy demand technologies

Transitioning towards a sustainable energy system requires the large-scale introduction of novel energy demand and supply technologies. Such novel technologies are often expensive at the point of their market introduction but eventually become cheaper due to technological learning. In order to quantify potentials for price and cost decline, the experience curve approach has been extensively applied to renewable and non-renewable energy supply technologies. However, its application to energy demand technologies is far less frequent. Here, we provide the first comprehensive review of experience curve analyses for energy demand technologies. We find a widespread trend towards declining prices and costs at an average learning rate of 18 ± 9%. This finding is consistent with the results for energy supply technologies and for manufacturing in general. Learning rates for individual energy demand technologies are symmetrically distributed around the arithmetic mean of the data sample. Absolute variation of learning rates within individual technology clusters of 7 ± 4%-points and between technology clusters of 7 ± 5%-points both contribute to the overall variability of learning rates. Our results show that technological learning is as important for energy demand technologies as it is for energy supply technologies. Applying the experience curve approach to forecast technology costs involves, however, unresolved uncertainties, as we demonstrate in a case study for the micro-cogeneration technology.     

Dismantling terrorist networks: Evaluating strategic options using agent-based modeling

Dismantling dark networks remains a critical goal for the peace and security of our society. Terrorist networks are the most prominent instantiation of dark networks, and they are alive and well. Attempts to preemptively disrupt these networks and their activities have met with both success and failure. In this paper, we examine the impacts of four common strategies for dismantling terrorist networks. The four strategies are: leader-focused, grassroots, geographic, and random. Each of these strategies has associated pros and cons, and each has different impacts on the structure and capabilities of a terrorist network. Employing a computational experimentation methodology, we simulate a terrorist network and test the effects of each strategy on the resiliency of that network. In addition, we test scenarios in which the terrorist network has (or does not have) information about an impending attack. Our work takes a structural perspective to the challenge of addressing terrorist networks. Specifically, we show how various strategies impact the structure of the network in terms of its resiliency and capacity to carry out future attacks. This paper also provides a valuable overview of how to use agent-based modeling for the study of complex problems in the terrorism, conflict studies, and security study domains.     

Limit to improvement: Myth or reality?: Empirical analysis of historical improvement on three technologies influential in the evolution of civilization

The evolution of civilization appears to have primarily resulted from continuous improvement made possible by technological advances. A group of social evolutionists and economists have identified, among others, energy, transport, as well as information and communication to be the three most influential technologies. On the other hand, a number of eminent scholars have cited several forces, natural, physiological, technological, as well as environmental which can place a limit on on-going improvement.The purpose of this paper is to empirically explore the continuous improvement process as well as the limit placed on these three technologies. Using the framework of both connected and disconnected multiple technology S-curves and X-factor, historical improvement data on these three elements have been analyzed. The results of our analysis indicate that improvement in general has continued without limit mainly due to a series of emerging new technologies. These emerging technologies can be either connected or disconnected from the existing mature technologies. Our preliminary analysis shows that much of the past improvement comes from new technologies that on first serious application appear to be substantially superior from earlier technologies. In addition, enormous continuous improvement, which has accompanied both connected and disconnected new technologies appear to have played the critical role in sustaining the evolution of civilization. The paper discusses a number of policy implications and suggests topics for future research.     

Organizational ambidexterity: Integrating deliberate and emergent strategy with scenario planning

In this article we propose scenario planning as a tool for fostering organizational ambidexterity. The concept of organizational ambidexterity continues to gain attention, however, clear methods for developing this organizational ability are generally not offered. We therefore describe organizational ambidexterity and situate it in the general strategy literature. Key characteristics of organizational ambidexterity are provided, and the logical link to scenario planning is made. As the concept of organizational ambidexterity is relatively novel, our proposal highlights the use of scenario planning as a potential tool for developing this organizational “skill”, and clear next steps are described to examine our proposal as well as leverage the concept of organizational ambidexterity beyond that of a simple metaphor.     

Discontinuous innovation capability accumulation in latecomer natural resource-processing firms

Most of the studies that describe the building of innovation capability in emerging and developing economies have focused on the ways in which latecomer firms develop continuously towards advanced capability levels along existing technological trajectories, particularly for the assembled products industries, especially in Asia. A slightly different approach is adopted herein by focusing on pathways of discontinuous capability building of firms in natural resource-processing industries. By drawing on evidence from a variety of case studies taken from 13 forestry, pulp, and paper firms in Brazil in the period 1950-2007, it was found that: (1) in contrast with the majority of case studies reported in the literature, the pathways followed by firms in their accumulation of innovation capability involved a qualitative departure from the established technological trajectory at an early stage in the development of their capability; (2) the pathways of firms along the new technological trajectories were nevertheless characterised by a high degree of variability (from intermediate to world leading innovators) in terms of the levels and speeds of the accumulation of innovation capability; (3) firms that have attained progressively higher levels of innovative performance have more rapidly developed a combination of internal and external research-based arrangements in order to undertake increasingly complex, but firm-centred innovation efforts. This paper sheds some light on some of the discussions that relate to the role of natural resources in the patterns of industrial progress and growth in those countries endowed with particular natural resource-based industries. It also provides a methodological contribution to the study of the long-term innovation strategies that make use of the dynamics of capability building, especially within natural resource-processing industries.     

A new methodology for the logistic analysis of evolutionary S-shaped processes: Application to historical time series and forecasting

A new multi-logistic methodology to analyze long range time series of evolutionary S-shaped processes is presented. It conceptually innovates over the traditional logistic approach. The ansatz includes computing the residuals to an optimized multi-logistic trend curve least squares fitted to the time-series data. The elements of the residuals series are checked for autocorrelations and once detected the residuals series is further analyzed to search for eventual presence of underlying periodic structures using a truncated Fourier sine series. The method foundations ensures both a universal applicability and a capacity to disclose the existence of active clocks that can be possibly traced to the driving motors of the evolutionary character of the time series, due to the responsiveness of corresponding process to the development of economic cycles. On associating these two views, it is found that the methodology has a strong potential to improve the quality of short-term forecasts. These findings have been put to test through applications of the methodology to studying the time evolution of two commodities of strong economic and social importance (corn and steel) and good results were consistently obtained for both the analytical and forecasting aspects.