A model of electronic commerce adoption by small voluntary organizations

The study discussed in this paper uses case studies of six small voluntary organizations to determine the primary factors that influence electronic commerce (EC) adoption. The findings indicate that perceived benefits, including efficiency, information sharing, marketing and increased donations have a strong influence on EC adoption. The results also indicate that organizational readiness, including ability to attract volunteers and/or in-kind donations, ability to raise funds, and strategic readiness had a positive influence on EC adoption. Consistent with prior research on EC adoption in the commercial sector, strong support was found for the influence of perceived pressure, including pressure from both internal and external stakeholders. The study also concluded that perceived social risks associated with the loss of human contact and the perception of dollars being diverted from client programs to finance the EC investment had a strong influence on EC adoption. Implications for EC adoption and future research on EC adoption in the voluntary sector are discussed.     

The future of information systems – <Emphasis Type="Italic">Thinking Informatically</Emphasis>

Many of those who are active within the academic field of information systems (IS) are constantly seeking a firm disciplinary basis for their endeavours. In many respects, such efforts are based upon a mistaken view of how disciplines are actually constituted, and the purposes that they serve. In many respects, it would be far more fruitful if those working within the field of IS were to accept a more fluid and contingent notion of a discipline; simultaneously recognizing the contested nature of many of the core concepts – particularly information, communication and technology. In so doing, we will be Thinking Informatically.     

<Emphasis Type="Italic">Essence</Emphasis>: facilitating software innovation

This paper suggests ways to facilitate creativity and innovation in software development. The paper applies four perspectives – Product, Project, Process, and People – to identify an outlook for software innovation. The paper then describes a new facility – Software Innovation Research Lab (SIRL) – and a new method concept for software innovation – Essence – based on views, modes, and team roles. Finally, the paper reports from an early experiment using SIRL and Essence and identifies further research.     

<Emphasis Type="Italic">i</Emphasis>SIM: An integrated design method for commercializing service innovation

Service innovation is focused on customer value creation. At its core, customer centric service innovation is technology-enabled, human-centered, and process-oriented. To profit from such innovation, firms need an integrated cross-disciplinary, holistic method to design and commercialize service innovation. From diverse but interrelated strands of theories from service science, strategic management, organization science and information systems literatures, this article develops a new integrated design method, known as iSIM (integrated Service Innovation Method), for simultaneous service innovation and business model design for sustained customer value co-creation with the firm. Following design science research method, the article theoretically defines and integrates iSIM’s seven constitutive design process-elements: service strategy, customer type / value proposition, service concept, service system, customer experience, service architecture and monetization into a coherent and end-to-end aligned integrated design method. It explains how iSIM would be holistically and iteratively practiced by practitioners, and conceptually exemplifies its utility via telco and Amazon case studies using secondary data. Perspectives on iSIM from selected practitioners are discussed which confirm iSIM’s potential utility for their business. Managerial implications of implementing the iSIM and potential areas for further research are also discussed.     

Consumer acceptance of RFID-enabled services: a model of multiple attitudes,perceived system characteristics and individual traits

The introduction of emerging technologies in retailing and their infusion in the service encounter necessitates research to better understand consumer attitudes towards the usage of technology in service delivery systems. The capability of Radio Frequency Identification (RFID) technology to automatically and uniquely identify products makes this technology promising as an enabler of innovative consumer services. However there is limited research on how consumers perceive the RFID-enabled service systems. The authors develop and empirically test a model that focuses on consumer attitudes towards technology-based services. Based on the pre-prototype user acceptance framework and using RFID as a focal technology, the proposed model includes a hierarchy of three distinct consumer attitudes: towards the general service concept, towards the general technology-based service application and towards the RFID-enabled service. Perceived system characteristics as well as personality traits are included in the model. The partial least squares method of structural equation modelling is used to analyse 575 questionnaires collected in two consumer surveys in Greece (n=173) and Ireland (N=402). The results of the study show that consumer attitude towards RFID-enabled services in retailing can be modelled as a confluence of multiple attitudes. The results also indicate that perceived system-related factors – such as performance and effort expectancy – as well as individual traits – such as technology anxiety and information privacy concern – affect consumer attitude towards technology-based and RFID-enabled services, respectively.     

Novel steganographic method based on generalized <Emphasis Type="Italic">K</Emphasis>-distance <Emphasis Type="Italic">N</Emphasis>-dimensional pixel matching

In this paper, a steganographic scheme adopting the concept of the generalized K _d -distance N-dimensional pixel matching is proposed. The generalized pixel matching embeds a B-ary digit (B is a function of K and N) into a cover vector of length N, where the order-d Minkowski distance-measured embedding distortion is no larger than K. In contrast to other pixel matching-based schemes, a N-dimensional reference table is used. By choosing d, K, and N adaptively, an embedding strategy which is suitable for arbitrary relative capacity can be developed. Additionally, an optimization algorithm, namely successive iteration algorithm (SIA), is proposed to optimize the codeword assignment in the reference table. Benefited from the high dimensional embedding and the optimization algorithm, nearly maximal embedding efficiency is achieved. Compared with other content-free steganographic schemes, the proposed scheme provides better image quality and statistical security. Moreover, the proposed scheme performs comparable to state-of-the-art content-based approaches after combining with image models.     

Greatest Lower Bound of System Failure Probability on a Special Time Interval Under Incomplete Information About the Distribution Function of the Time to Failure of the System

The author solves the problem of finding greatest lower bounds for the probability F (??) – F (u),0 < u <, ?? < ∞, where \( u= m-{\upsigma}_{\mu}3\sqrt{3},\kern0.5em \upupsilon = m+{\upsigma}_{\mu}3\sqrt{3},\kern0.5em \mathrm{and}\kern0.5em {\upsigma}_{\mu} \) is a fixed dispersion in the set of distribution functions F (x) of non-negative random variables with unimodal differentiable density with mode m and two first fixed moments μ ₁ and μ ₂. The case is considered where the mode coincides with the first moment: m = μ ₁. The greatest lower bound of all possible greatest lower bounds for this problem is obtained and it is nearly one, namely, 0.98430.     

Assessment of crowdsourcing and gamification loss in user-assisted object segmentation

There has been a growing interest in applying human computation – particularly crowdsourcing techniques – to assist in the solution of multimedia, image processing, and computer vision problems which are still too difficult to solve using fully automatic algorithms, and yet relatively easy for humans. In this paper we focus on a specific problem – object segmentation within color images – and compare different solutions which combine color image segmentation algorithms with human efforts, either in the form of an explicit interactive segmentation task or through an implicit collection of valuable human traces with a game. We use Click’n’Cut, a friendly, web-based, interactive segmentation tool that allows segmentation tasks to be assigned to many users, and Ask’nSeek, a game with a purpose designed for object detection and segmentation. The two main contributions of this paper are: (i) We use the results of Click’n’Cut campaigns with different groups of users to examine and quantify the crowdsourcing loss incurred when an interactive segmentation task is assigned to paid crowd-workers, comparing their results to the ones obtained when computer vision experts are asked to perform the same tasks. (ii) Since interactive segmentation tasks are inherently tedious and prone to fatigue, we compare the quality of the results obtained with Click’n’Cut with the ones obtained using a (fun, interactive, and potentially less tedious) game designed for the same purpose. We call this contribution the assessment of the gamification loss, since it refers to how much quality of segmentation results may be lost when we switch to a game-based approach to the same task. We demonstrate that the crowdsourcing loss is significant when using all the data points from workers, but decreases substantially (and becomes comparable to the quality of expert users performing similar tasks) after performing a modest amount of data analysis and filtering out of users whose data are clearly not useful. We also show that – on the other hand – the gamification loss is significantly more severe: the quality of the results drops roughly by half when switching from a focused (yet tedious) task to a more fun and relaxed game environment.     

Knowledge State Algorithms

We introduce the novel concept of knowledge states. The knowledge state approach can be used to construct competitive randomized online algorithms and study the trade-off between competitiveness and memory. Many well-known algorithms can be viewed as knowledge state algorithms. A knowledge state consists of a distribution of states for the algorithm, together with a work function which approximates the conditional obligations of the adversary. When a knowledge state algorithm receives a request, it then calculates one or more “subsequent” knowledge states, together with a probability of transition to each. The algorithm uses randomization to select one of those subsequents to be the new knowledge state. We apply this method to randomized k-paging. The optimal minimum competitiveness of any randomized online algorithm for the k-paging problem is the kth harmonic number, \(H_{k}=\sum^{k}_{i=1}\frac{1}{i}\). Existing algorithms which achieve that optimal competitiveness must keep bookmarks, i.e., memory of the names of pages not in the cache. An H _k -competitive randomized algorithm for that problem which uses O(k) bookmarks is presented, settling an open question by Borodin and El-Yaniv. In the special cases where k=2 and k=3, solutions are given using only one and two bookmarks, respectively.     

Translation-based approaches for solving disjunctive temporal problems with preferences

Disjunctive Temporal Problems (DTPs) with Preferences (DTPPs) extend DTPs with piece-wise constant preference functions associated to each constraint of the form l ≤ x ? y ≤ u, where x,y are (real or integer) variables, and l,u are numeric constants. The goal is to find an assignment to the variables of the problem that maximizes the sum of the preference values of satisfied DTP constraints, where such values are obtained by aggregating the preference functions of the satisfied constraints in it under a “max” semantic. The state-of-the-art approach in the field, implemented in the native DTPP solver Maxilitis, extends the approach of the native DTP solver Epilitis. In this paper we present alternative approaches that translate DTPPs to Maximum Satisfiability of a set of Boolean combination of constraints of the form l?x ? y?u, ? ∈{<,≤}, that extend previous work dealing with constant preference functions only. We prove correctness and completeness of the approaches. Results obtained with the Satisfiability Modulo Theories (SMT) solvers Yices and MathSAT on randomly generated DTPPs and DTPPs built from real-world benchmarks, show that one of our translation is competitive to, and can be faster than, Maxilitis (This is an extended and revised version of Bourguet et al. 2013).     

On the Complexity of Fibonacci Coding

We show that converting an n-digit number from a binary to Fibonacci representation and backward can be realized by Boolean circuits of complexity O(M(n) log n), where M(n) is the complexity of integer multiplication. For a more general case of r-Fibonacci representations, the obtained complexity estimates are of the form \({2^O}{(\sqrt {\log n} )_n}\).     

Optimal Path Embedding in the Exchanged Crossed Cube

The (s + t + 1)-dimensional exchanged crossed cube, denoted as ECQ(s, t), combines the strong points of the exchanged hypercube and the crossed cube. It has been proven that ECQ(s, t) has more attractive properties than other variations of the fundamental hypercube in terms of fewer edges, lower cost factor and smaller diameter. In this paper, we study the embedding of paths of distinct lengths between any two different vertices in ECQ(s, t). We prove the result in ECQ(s, t): if s ≥ 3, t ≥ 3, for any two different vertices, all paths whose lengths are between \( \max \left\{9,\left\lceil \frac{s+1}{2}\right\rceil +\left\lceil \frac{t+1}{2}\right\rceil +4\right\} \) and 2 ^s+t+1 ? 1 can be embedded between the two vertices with dilation 1. Note that the diameter of ECQ(s, t) is \( \left\lceil \frac{s+1}{2}\right\rceil +\left\lceil \frac{t+1}{2}\right\rceil +2 \). The obtained result is optimal in the sense that the dilations of path embeddings are all 1. The result reveals the fact that ECQ(s, t) preserves the path embedding capability to a large extent, while it only has about one half edges of CQ _n .     

Efficient and secure multi secret sharing schemes based on boolean XOR and arithmetic modulo

Multi Secret Sharing (MSS) scheme is an efficient method of transmitting more than one secret securely. In (n, n)-MSS scheme n secrets are used to create n shares and for reconstruction, all n shares are required. In state of the art schemes n secrets are used to construct n or n + 1 shares, but one can recover partial secret information from less than n shares. There is a need to develop an efficient and secure (n, n)-MSS scheme so that the threshold property can be satisfied. In this paper, we propose three different (n, n)-MSS schemes. In the first and second schemes, Boolean XOR is used and in the third scheme, we used Modular Arithmetic. For quantitative analysis, Similarity metrics, Structural, and Differential measures are considered. A proposed scheme using Modular Arithmetic performs better compared to Boolean XOR. The proposed (n, n)-MSS schemes outperform the existing techniques in terms of security, time complexity, and randomness of shares.     

The formula of the solution for some classes of initial boundary value problems for the hyperbolic equation with two independent variables

A new representation is proved of the solutions of initial boundary value problems for the equation of the form u _xx (x, t) + r(x)u _x (x, t) ? q(x)u(x, t) = u _tt (x, t) + μ(x)u _t (x, t) in the section (under boundary conditions of the 1st, 2nd, or 3rd type in any combination). This representation has the form of the Riemann integral dependent on the x and t over the given section.     

Almost cover-free codes

We say that an s-subset of codewords of a code X is (s, l)-bad if X contains l other codewords such that the conjunction of these l words is covered by the disjunction of the words of the s-subset. Otherwise, an s-subset of codewords of X is said to be (s, l)-bad. A binary code X is called a disjunctive (s, l) cover-free (CF) code if X does not contain (s, l)-bad subsets. We consider a probabilistic generalization of (s, l) CF codes: we say that a binary code is an (s, l) almost cover-free (ACF) code if almost all s-subsets of its codewords are (s, l)-good. The most interesting result is the proof of a lower and an upper bound for the capacity of (s, l) ACF codes; the ratio of these bounds tends as s→∞ to the limit value log₂ e/(le).     

Interactive Restless Multi-armed Bandit Game and Swarm Intelligence Effect

We obtain the conditions for the emergence of the swarm intelligence effect in an interactive game of restless multi-armed bandit (rMAB). A player competes with multiple agents. Each bandit has a payoff that changes with a probability p _c per round. The agents and player choose one of three options: (1) Exploit (a good bandit), (2) Innovate (asocial learning for a good bandit among n _I randomly chosen bandits), and (3) Observe (social learning for a good bandit). Each agent has two parameters (c, p _obs ) to specify the decision: (i) c, the threshold value for Exploit, and (ii) p _obs , the probability for Observe in learning. The parameters (c, p _obs ) are uniformly distributed. We determine the optimal strategies for the player using complete knowledge about the rMAB. We show whether or not social or asocial learning is more optimal in the (p _c , n _I ) space and define the swarm intelligence effect. We conduct a laboratory experiment (67 subjects) and observe the swarm intelligence effect only if (p _c , n _I ) are chosen so that social learning is far more optimal than asocial learning.     

Procedural content generation for platformers: designing and testing FUN PLEdGE

Video games are a peculiar medium, standing at the crossing point between art and software application, and characterized by an active involvement of its audience. The complexity of the product generates a huge challenge for the companies that develop video games. In the development process, level designers play a crucial role: they are in charge of declining the theoretical framework developed by the game designer into game levels, which contain the actual gameplay scenarios. Hence, the final goal of any level designer is to valorize the game design by creating enjoyable gaming experiences while, at the same time, respecting several constraints. To lighten the burden on level designers, several semi-automated approaches to level generation have appeared in time, but the majority of these tools suffer from several drawbacks. In the present work, we tackle the issue of designing, prototyping and testing FUN PLEdGE, a general-purpose automated levels generator and editor for platform video games. Its main goal is to shrink development time while producing – unassisted – levels that are both playable and fun. Moreover, our tool provides the maximum freedom to the level designer, by avoiding to impose unnecessary constraints on the structure of the levels and by guaranteeing the possibility to modify and personalize by hand the generated levels. During this process, the generator assists the designer by suggesting corrections functional to the quality of the player experience. To prove the effectiveness of our prototypal application we have also developed and tested with players a platform game. In the same vein, we asked to a group of game developers to test FUN PLEdGE.     

The weight-constrained maximum-density subtree problem and related problems in trees

Given a tree T=(V,E) of n nodes such that each node v is associated with a value-weight pair (val _v ,w _v ), where value val _v is a real number and weight w _v is a non-negative integer, the density of T is defined as \(\frac{\sum_{v\in V}{\mathit{val}}_{v}}{\sum_{v\in V}w_{v}}\). A subtree of T is a connected subgraph (V′,E′) of T, where V′?V and E′?E. Given two integers w _min? and w _max?, the weight-constrained maximum-density subtree problem on T is to find a maximum-density subtree T′=(V′,E′) satisfying w _min?≤∑_v∈V′ w _v ≤w _max?. In this paper, we first present an O(w _max? n)-time algorithm to find a weight-constrained maximum-density path in a tree T, and then present an O(w _max? ² n)-time algorithm to find a weight-constrained maximum-density subtree in T. Finally, given a node subset S?V, we also present an O(w _max? ² n)-time algorithm to find a weight-constrained maximum-density subtree in T which covers all the nodes in S.     

Bounded Unpopularity Matchings

We investigate the following problem: given a set of jobs and a set of people with preferences over the jobs, what is the optimal way of matching people to jobs? Here we consider the notion of popularity. A matching M is popular if there is no matching M′ such that more people prefer M′ to M than the other way around. Determining whether a given instance admits a popular matching and, if so, finding one, was studied by Abraham et al. (SIAM J. Comput. 37(4):1030–1045, 2007). If there is no popular matching, a reasonable substitute is a matching whose unpopularity is bounded. We consider two measures of unpopularity—unpopularity factor denoted by u(M) and unpopularity margin denoted by g(M). McCutchen recently showed that computing a matching M with the minimum value of u(M) or g(M) is NP-hard, and that if G does not admit a popular matching, then we have u(M)≥2 for all matchings M in G.Here we show that a matching M that achieves u(M)=2 can be computed in \(O(m\sqrt{n})\) time (where m is the number of edges in G and n is the number of nodes) provided a certain graph H admits a matching that matches all people. We also describe a sequence of graphs: H=H ₂,H ₃,…,H _k such that if H _k admits a matching that matches all people, then we can compute in \(O(km\sqrt{n})\) time a matching M such that u(M)≤k?1 and \(g(M)\le n(1-\frac{2}{k})\). Simulation results suggest that our algorithm finds a matching with low unpopularity in random instances.     

A rough <Emphasis Type="Italic">ν</Emphasis>-twin support vector regression machine

After combining the ν-Twin Support Vector Regression (ν-TWSVR) with the rough set theory, we propose an efficient Rough ν-Twin Support Vector Regression, called Rough ν-TWSVR for short. We construct a pair of optimization problems which are motivated by and mathematically derived from a related ν-TWSVR Rastogi et al. (Appl Intell 46(3):670–683 2017) and Rough ν-SVR Zhao et al. (Expert Syst Appl 36(6):9793–9798 2009). Rough ν-TWSVR not only utilizes more data information rather than the extreme data points in the ν-TWSVR, but also makes different points having different effects on the regressor depending on their positions. This method can implement the structural risk minimization and automatically control accuracies according to the structure of the data sets. In addition, the double ε s are utilized to construct the rough tube for upper(lower)-bound Rough ν-TWSVR instead of a single ε in the upper(lower)-bound ν-TWSVR. Moreover, This rough tube consisting of positive region, boundary region, and negative region yields the feasible set of the Rough ν-TWSVR larger than that of the ν-TWSVR, which makes the objective function of the Rough ν-TWSVR no more than that of ν-TWSVR. The Rough ν-TWSVR improves the generalization performance of the ν-TWSVR, especially for the data sets with outliers. Experimental results on toy examples and benchmark data sets confirm the validation and applicability of our proposed Rough ν-TWSVR.