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The paper's aim is to provide information about mobile viruses for end‐users or organizations and recommend useful tips of how individuals can protect their mobile phones from the intrusion of mobile phone viruses.

This paper surveys chronicle, securities, risks and countermeasure of mobile phone viruses.

This paper investigates infection routes, threats, damage, and spreading ways of mobile phone viruses and provides available countermeasures. It also provides useful tips about mobile viruses, indicating what to do and how to do it.

This research may not be exhaustive about mobile viruses.

A very useful source of information and impartial advice for end‐users or organizations who are planning to protect their mobile phones and their own privacy.

This paper is the first to survey the risk of mobile phones and it discusses how organizations or individuals can protect mobile phones from the intrusion of viruses and how to develop their own mobile virus security plan.

The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan warehousing strategies. More than practically required storage space has been identified as wastes, and also it does not improve performance. An organized framework integrating storage design policies, operational performance and customer value improvement for retail-distribution management is lacking. Therefore, the purpose of this paper is to develop broad guidelines to design the “just-right” amount of forward area, i.e., “lean buffer” answering the following questions: “What should be lean buffer size? How effective the forward area is? As per demand variations, which storage waste (SKU) should be allocated with how much storage space? What is the amount of storage waste (SW)? How smooth the material flow is in between reserve-forward area?” for storage allocation in cosmetics distribution centers.

After forecasting static storage allocation between two planning horizons, if a particular SKU is less or non-moving, then it will cause SW, as the occupied location can be utilized by other competing SKUs, and also it impedes material flow for an instance. A dynamically efficient and self-adaptive, knapsack instance based heuristics is developed in order to make effective storage utilization.

The existing state-of-the-art under study is supported with a distribution center case, and the study investigates the need of a model adopting lean management approach in storage allocation policies along with test results in LINGO. The sensitivity analysis describes the impact of varying demand and buffer size on performance. The results are compared with uniform and exponential distributed demands, and findings reveal that the proposed heuristics improves efficiency and reduce SWs in forward-reserve area.

The presented model demonstrates a novel thinking of lean adoption in designing storage allocation strategy and its performance measures while reducing wastes and improving customer value. Future research issues are highlighted, which may be of great help to the researchers who would like to explore the emerging field of lean adoption for sustainable retail and distribution operations.

The contemporary e-tailing marketplace insists that distribution centers are playing the roles of both wholesalers and retailers which require different storage-handling load sizes due to different product variants. To fulfill piecewise retail orders, a separate small size-fast pick area is design called “forward buffer” wherein pallets are allocated from reserve area. Due to non-uniform pallets, the static allocation policy diminishes forward space utilization and also, more than practically required buffer size has been identified as wastage. Thus, dynamic storage allocation policy is required to design for reducing storage wastage and improving throughput considering non-uniform unit load sizes. The purpose of this paper is to model such policy and develop an e-decision support system assisting enterprise practitioners with real-time decision making.

The research method is developed as a dynamic storage allocation policy and mathematical modeled as knapsack-based heuristics. The execution procedure of policy is explained as an example and tested with case-specific data. The developed model is implemented as a web-based support system and tested with rational data instances, as well as overcoming prejudices against single case findings.

The provided model considers variable size storage-handling unit loads and recommends number of pallets allocations in forward area reducing storage wastes. The algorithm searches and suggests the “just-right” amount of allocations for each product balancing existing forward capacity. It also helps to determine “lean buffer” size for forward area ensuring desired throughput. Sensitivity and buffer performance analysis is carried out for Poisson distributed data sets followed by research synthesis.

Warehouse practitioners can use this model ensuring a desired throughput level with least forward storage wastages. The model driven e-decision support system (DSS) helps for effective real-time decision making under complicated business scenarios wherein products are having different physical dimensions. It assists the researchers who would like to explore the emerging field of “lean” adoption in enterprise information and retail-distribution management.

The paper provides an inventive approach endorsing lean thinking in storage allocation policy design for a forward-reserve model. Also, the developed methodology incorporating features of e-DSS along with quantitative modeling is an inimitable research contribution justifying rational data support.

Studies on transfers to a more regulated section show an increase in information disclosure and stocks’ liquidity levels. Classical theories suggest that volatility should also be reduced. This study aims to analyse the long-term effects of a section transfer to a more regulated section (TSE 1/TSE 2) on stock return volatility.

This study uses an empirical framework relying on two-sample t-tests and panel regressions. These use robust standard errors and control for fixed effects, day effects and macroeconomic factors. The return variance of comparable stocks’ benchmark sample, instead of market variance, is used as a control variable. Comparable stocks operate within the same industry and do not transfer during the sample period. The authors test our results’ robustness using generalized autoregressive conditional heteroskedasticity estimates.

The study’s main findings show that pre-transferred stocks are more volatile than the stocks’ benchmark sample. The transfer to a more regulated section leads to a gradual decrease in the total daily stock return volatility, intraday return volatility and overnight return volatility.

To the best of my knowledge, this study is the first to empirically address the volatility change caused by the stocks’ transfer to a more regulated section. This study highlights the benefits of choosing section transfers to reduce volatility.

The purpose of this paper is to examine the underlying mechanisms of how consumers respond to health-claim framing via experimental design.

Across the two experiments conducted for this research, the authors examine the moderating effects of self-perceived health status and individuals’ need for cognition on health-claim framing.

The results indicate that personal differences moderate the effects of health-claim framing on consumers’ food-product evaluation. Consumers with poor health status evaluate food product more favorably when the reduced-disease-risk claims are offered. However, consumers with good health status evaluate food product similarly between the two health claims. Moreover, consumers with a high need for cognition evaluate food product more favorably when the reduced-disease-risk claims are used, whereas consumers with a low need for cognition evaluate food product more favorably when the enhance function claims are used.

This research provides that reduced-disease-risk claims may be the better communication message used to persuade consumers no matter they rate themselves as poor health status or good health status. Moreover, the results of the present research also indicate the importance of market segmentation. Marketers could design proper advertisements and select the appropriate media vehicles for low need for cognition readers and high need for cognition readers separately.

There has been few studies addressed consumers’ product choice with respect to different health-claim framing. Further, this research presents a new concept of the effects between individual differences and health-claim framing on consumers’ food-product evaluation.

Nowadays, diversity management in business organizations becomes so imperative in a time-sensitive business. However, diversity should not be measured as a static number. To better understand the fast-changing terrain, the paper aims to strongly propose using the tracking signal method to dynamically monitor the efficiency performance in regard to the future of diversity and best practices. This will allow diversity to play a more strategic role in cultivating sustainable business growth.

The paper employs the tracking signal, widely used to monitor the performance of a forecasting model, with some extension to dynamically monitor the technical efficiency due to its ability in alarming out-of-control signals.

The approach is considered as a quantitative, objective and reasonable evaluation system because it can quickly alert employees with inferior performance and promote those with persistently outstanding performance. It also provides managers the right timing to find assignable causes affecting their workers' performance. Most importantly, it can be unsophisticatedly implemented in many aspects of efficiency evaluation for assisting organizations to improve their competitive power through efficiency gains and well expedite their broadly managerial decisions.

The majority of previous researches aggregate multi-dimensional efficiencies by different weighting strategies into a single index before making their judgments. These approaches mainly focus on the first phase of the decision-making procedure by considering the efficiency in a static-state. As efficiency is time-sensitive, it should be evaluated dynamically. Thus, serving as the second phase of the procedure, the method is a complement of previous researches.