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Human resource technologies in the hospitality industry are a means by which an organization can gain competitive advantage technologically. The technology-oriented human capital embedded in an organization's human resources is a source of sustainable competitive advantage in an industry that is heavily dependent on people and makes it unique and inimitable. This study uses data collected on 34 different practices to provide a snapshot of current practices in the hospitality sector, which can be used to benchmark individual technology operations against the current norms. The paper aims to discuss these issues.

This paper uses survey data collected from dozens of managers working in the hospitality sector on the level of outsourcing of 34 different HRM practices to provide a snapshot of current practices in the hospitality sector.

Starting with the theoretical predictions of total cost of ownership and transaction cost analysis, multiple regression models are used to test whether or not human resource outsourcing (HRO) technology-related activities in hospitality are associated with negative outcomes, such as higher voluntary turnover of good employees.

This is one of the first articles to explore HRO technology in the hospitality sector and the findings suggest that what an organization outsources matters.

These results can be used by hospitality managers to benchmark their operations against the current HRO technology norms.

It is expected that the type of HR technology-related activities outsourced in hospitality will affect how employees and employers view and react to HRO in hospitality.

The (A) case describes the evolution between 1999 and 2005 of an unusual innovation team within the office of the chief information officer at oil and gas giant BP. This team helped business units conceive, develop, and implement novel, value-added applications for emerging information technologies. The team leader, vice president and chief technology officer Phiroz Darukhanavala (“Daru”), eschewed a large group and venture budget in favor of a small, lean team intimately engaged with BP's business units. The case describes several mechanisms created by the CTO office during its early evolution: “Blue Chalk” events that expanded executives' appreciation of emerging technology capabilities, a network of relationships through which emerging technologies were scouted and vetted, a structured technology transfer process, and annual “game-changer” projects.

The (B) case describes how the CTO office team members in 2011 again solicited advice from their ecosystem of thought leaders and held workshops to significantly enhance their impact. As a result, they began developing solutions for broader, more fundamental business problems that came to be known as Grand Challenges: extremely difficult business problems whose solutions could potentially create hundreds of millions—or billions—of dollars in business value.

After reading and analyzing the case, students will be able to:

• Understand the management challenges associated with realizing the business value of new technologies

• Explore how innovation management evolves as an innovation team learns from its successes and failures and, more importantly, builds a reputation within and outside the company

• Examine a prototypical “advocate” model of corporate entrepreneurial practice

• Explore a leading example of a successful internal innovation program

Understand the management challenges associated with realizing the business value of new technologies

Explore how innovation management evolves as an innovation team learns from its successes and failures and, more importantly, builds a reputation within and outside the company

Examine a prototypical “advocate” model of corporate entrepreneurial practice

Explore a leading example of a successful internal innovation program

Due to the miniaturization of electronic devices, the increased current density through solder joints leads to the occurrence of electromigration failure, thereby reducing the reliability of electronic devices. The purpose of this study is to propose a finite element-artificial neural network method for the prediction of temperature and current density of solder joints, and thus provide reference information for the reliability evaluation of solder joints.

The temperature distribution and current density distribution of the interconnect structure of electronic devices were investigated through finite element simulations. During the experimental process, the actual temperature of the solder joints was measured and was used to optimize the finite element model. A large amount of simulation data was obtained to analyze the neural network by varying the height of solder joints, the diameter of solder pads and the magnitude of current loads. The constructed neural network was trained, tested and optimized using this data.

Based on the finite element simulation results, the current is more concentrated in the corners of the solder joints, generating a significant amount of Joule heating, which leads to localized temperature rise. The constructed neural network is trained, tested and optimized using the simulation results. The ANN 1, used for predicting solder joint temperature, achieves a prediction accuracy of 96.9%, while the ANN 2, used for predicting solder joint current density, achieves a prediction accuracy of 93.4%.

The proposed method can effectively improve the estimation efficiency of temperature and current density in the packaging structure. This method prevails in the field of packaging, and other factors that affect the thermal, mechanical and electrical properties of the packaging structure can be introduced into the model.

Just imagine … you are sitting down to a quiet, restful dinner after a hard day at the office. Your food is ready, and all thoughts of work are banished. Until the phone rings. To ignore it is out of the question. Why? Because you are a member of a hi‐tech, 24 hour virtual team who must be available as and when required by other group members. The concept of virtual teaming has been around for over 20 years, but with the upsurge of globalization and the recent wave of technological developments it has taken on a new impetus. So what has changed? And is this type of teaming really as effective as some organizations claim?

Just imagine … you are sitting down to a quiet, restful dinner after a hard day at the office. Your food is ready, and all thoughts of work are banished. Until the phone rings. To ignore it is out of the question. Why? Because you are a member of a hi‐tech, 24‐hour virtual team who must be available as and when required by other group members. The concept of virtual teaming has been around for over 20 years, but with the upsurge of globalization and the recent wave of technological developments it has taken on a new impetus. So what has changed? And is this type of teaming really as effective as some organizations claim?

The purpose of this article is to advance critical debate in relation to a very critical issue in current healthcare management – namely “patient safety”. This is currently a very high profile issue. In its various guises such as clinical governance, integrated governance and healthcare governance the question of avoiding or at least minimising harm to patients is attracting a huge amount of attention. Considerable resources especially within the acute sector are allocated to the problem. But, despite the systematic attention, progress in healthcare compared with certain other sectors is slow and mistakes continue to occur. Hospital acquired infections and clinical errors have become a matter of acute public concern. Evaluations of the health service are critically influenced by adverse judgements on this dimension of care.

The authors draw primarily upon relevant literature in order to make sense of recent empirical research in eight acute hospital trusts in the UK. The analysis, however, is relevant to healthcare systems around the world.

The authors reveal how the massive investment in systems, service improvement mechanisms and clinical government regimes may not in themselves be enough. One reason why they may not be enough is that there can be a problem of gaining acceptance and legitimacy. Staff may see such managers as “policing” and “interfering”. There is then the danger of a vicious circle – more control but less effective control because of a feeling of alienation. The policing element is at best a final safety net not the prompt for improvement. They then identify six barriers and each is accompanied by a recommendation for its resolution.

There are a number of implications for practice and for systems reform, which stem from the analysis. Two main recommendations stand out: they need to be handled together. First, the traditional model of the autonomous professional needs to be challenged by subjecting clinical practice to shared clinical governance procedures. Second, and simultaneously, there is a need to attend to underlying values. There is a need to revisit the issue of underpinning values so that clinical values and system‐wide/managerial values are congruent rather than separate or even in conflict. At this point, governance and leadership should come together.

This paper provides useful information from the literature on current healthcare management.

British government approves data network After months of preparation by HM Treasury's Central Computer and Telecommunications Agency (CCTA), the first phase of the Government Data Network (GDN) has now been accepted. Trials of GDN took place in January, and it has now been implemented for daily use in 178 Customs and Excise locations throughout Britain. GDN is operated by Racal Data Networks.

To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network.

First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals and temperature drift signals. Then, TFPF denoises the mixed-signal, the noise signal is directly removed and the denoised sub-sequence is reconstructed, which is used as training data to train the MEA optimized BP to obtain a temperature drift compensation model. Finally, the gyro’s temperature characteristic sequence is processed by the trained model.

The experimental result proved the superiority of this method, the bias stability value of the compensation signal is 1.279 × 10^–3°/h and the angular velocity random walk value is 2.132 × 10^–5°/h/vHz, which is improved compared to the 3.361°/h and 1.673 × 10^–2°/h/vHz of the original output signal of the gyro.

This study proposes a multi-dimensional processing method, which treats different noises separately, effectively protects the low-frequency characteristics and provides a high-precision training set for drift modeling. TFPF can be optimized by SEVMD parallel processing in reducing noise and retaining static characteristics, MEA algorithm can search for better threshold and connection weight of BP network and improve the model’s compensation effect.