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Technological disruptions such as the Internet of Things and autonomous devices, enhanced analytical capabilities (artificial intelligence) and rich media (virtual and augmented reality) are creating smart environments that are transforming industry structures, processes and practices. The purpose of this paper is to explore critical technological advancements using a value co-creation lens to provide insights into service innovations that impact ecosystems. The paper provides examples from tourism and hospitality industries as an information dependent service management context.

The research synthesizes prevailing theories of co-creation, service ecosystems, networks and technology disruption with emerging technological developments.

Findings highlight the need for research into service innovations in the tourism and hospitality sector at both macro-market and micro-firm levels, emanating from the rapid and radical nature of technological advancements. Specifically, the paper identifies three areas of likely future disruption in service experiences that may benefit from immediate attention: extra-sensory experiences, hyper-personalized experiences and beyond-automation experiences.

Tourism and hospitality services prevail under varying levels of infrastructure, organization and cultural constraints. This paper provides an overview of potential disruptions and developments and does not delve into individual destination types and settings. This will require future work that conceptualizes and examines how stakeholders may adapt within specific contexts.

Technological disruptions impact all facets of life. A comprehensive picture of developments here provides policymakers with nuanced perspectives to better prepare for impending change.

Guest experiences in tourism and hospitality by definition take place in hostile environments that are outside the safety and familiarity of one’s own surroundings. The emergence of smart environments will redefine how customers navigate their experiences. At a conceptual level, this requires a complete rethink of how stakeholders should leverage technologies, engage and reengineer services to remain competitive. The paper illustrates how technology disrupts industry structures and stimulates value co-creation at the micro and macro-societal level.

The purpose of this paper is to examine the long-term cointegrating relationship between ocean, rail, truck and air cargo freight rates, as well as the short-term dynamics between these four series. The authors also test the predictive ability of these freight rates on major economic indicators.

The authors employ a vector error-correction model using 16 years of monthly time series data on freight rate data in the ocean, truck, rail and air cargo sectors to examine the interrelationship between these series as well as their interrelationship with major economic indicators.

The authors find that truck freight rates and as well as dry bulk freight rates have the strongest predictive power over other transportation freight rates as well as for the four major economic indicators used in this study. The authors find that dry bulk freight rates lead other freight rates in the short-run but lag other freight rates in the long run.

While ocean freight rate time series have been examined in a large number of studies, little research has been done on the interrelationship between ocean freight rates and the freight rates of other modes of transportation. Through the use of data on five different freight rate series, the authors are able to assess which rates lead and which rates lag each other and thus assist future researchers and practitioners forecast freight rates. The authors are also one of the few studies to assess the predictive power of non-ocean freight rates on major economic indicators.

This research analyzes the cycle of the dry bulk shipping market (DBSM) as a representative of spot and period charter rates in dry bulk shipping to develop strategies for investment timing (i.e. asset play) and fleet trading (chartering strategy).

Spectral analysis is a numerical approach to extract significant cyclicality, which may be utilized to develop trading strategies. Instead of working with a single dataset (univariate), a system approach can be utilized to observe a significant shipping market cycle in its multi-variate circumstance. In this paper, a system dynamics design is employed to extract cyclicality in the DBSM in its particular industrial environment. The system dynamic design has competitive forecasting accuracy relative to univariate time series models and artificial neural networks (ANNs) in terms of forecasting outcomes.

The results show that the system dynamic design has a better forecasting performance according to three evaluation metrics, mean absolute scale error (MASE), root mean square error (RMSE) and mean absolute percentage error (MAPE).

Cyclical analysis is a significantly useful instrument for shipping asset management, particularly in market entry–exit operations. This paper investigated the cyclical nature of the dry bulk shipping business and estimated significant business cycle periodicity at around 4.5-year frequency (i.e. the Kitchin cycle).

eScience workflows use orchestration for integrating and coordinating distributed and heterogeneous scientific resources, which are increasingly exposed as web services. The rate of growth of scientific data makes eScience workflows data‐intensive, challenging existing workflow solutions. Efficient methods of handling large data in scientific workflows based on web services are needed. The purpse of this paper is to address this issue.

In a previous paper the authors proposed Data‐Flow Delegation (DFD) as a means to optimize orchestrated workflow performance, focusing on SOAP web services. To improve the performance further, they propose pipelined data‐flow delegation (PDFD) for web service‐based eScience workflows in this paper, by leveraging from the domain of parallel programming. Briefly, PDFD allows partitioning of large datasets into independent subsets that can be communicated in a pipelined manner.

The results show that the PDFD improves the execution time of the workflow considerably and is capable of handling much larger data than the non‐pipelined approach.

Execution of a web service‐based workflow hampered by the size of data can be facilitated or improved by using services supporting Pipelined Data‐Flow Delegation.

Contributions of this work include the proposed concept of combining pipelining and Data‐Flow Delegation, an XML Schema supporting the PDFD communication between services, and the practical evaluation of the PDFD approach.

Healthcare facility managers work in complex and dynamic environments where critical decisions are constantly made. Providing them with enhanced decision support systems would result in a positive impact on the productivity and success of the projects they undertake, as well as the sustainability of critical healthcare infrastructure. The purpose of this paper is to propose a conceptual ambient intelligent environment for enhancing the decision-making process of the facility managers. This low-cost data-rich environment would use building information modeling (BIM) and mobile augmented reality (MAR) as technological bases for the natural human-computer interfaces and aerial drones as technological tools.

This paper presents a scenario for the integration of augmented reality (AR) and building information modeling (BIM) to build an ambient intelligent (AmI) environment for facility managers where mobile, natural, user interfaces would provide the users with required data to facilitate their critical decision-making process. The technological requirements for having such an intelligent environment are also discussed.

The proposed BIM-MAR-based approach is capable of enhancing maintenance related practices for facility managers who are mobile to integrate with their facilities' intelligent environment. This approach is also capable of providing a collaborative environment in which different stakeholders, across geographically distributed areas, could work together to solve facility management tasks.

In this paper ambient intelligence will be considered for the first time in the area of healthcare facility management practices to provide facility managers with an intelligent BIM-based environment to access facility information and consequently enhance their decision-making process.