Future Performance Research Articles

How do strategic alliance formations create shareholder value? An application of the event study methodology in the B2B context

By announcing the formation of business-to-business (B2B) relationships, such as strategic alliances, firms send signals to market observers who form expectations about these firms' future performance, ultimately affecting their shareholder value. The use of an event study methodology enables scholars to gauge the extent of the shareholder value these relationships can create. The role of the present study is twofold. First, we aim to systematically investigate the relationship between strategic alliance formations and firm shareholder value, identifying conditions under which strategic alliances create or even destroy value, including factors related to the firms and alliances as well as their interactions. Our second objective is to explain how B2B marketing researchers can apply the event study methodology in the context of strategic alliances. We provide a detailed explanation of how scholars can apply an event study methodology to strategic alliances, and B2B relationships more broadly, taking into account the research area-specific considerations, such as the appropriate modeling approach, variable coding, and event and estimation windows.

Mutual Fund Partial Liquidation and Future Performance

Mutual Fund Partial Liquidation and Future Performance

Applications of Deep Learning Models for Forecasting and Modelling Rainwater in Moscow

To model and forecast complex time series data, machine learning has become a major field. This machine learning study examined Moscow rainfall data's future performance. The dataset is split into 65% training and 35% test sets to build and validate the model. We compared these deep learning models using the Root Mean Square Error (RMSE) statistic. The LSTM model outperforms the BILSTM and GRU models in this data series. These three models forecast similarly. This information could aid the creation of a complete Moscow weather forecast book. This material would benefit policymakers and scholars. We also believe this study can be used to apply machine learning to complex time series data, transcending statistical approaches.

Testing the Hedging Effectiveness of Gold Derivative Market in India

The purpose of this article is to estimate the hedging effectiveness of the Indian Gold Derivative Market from both the statistics of Static hedge methodology of Vector Error Correction Method and Time-Varying hedge methodology of DVEC-GARCH, covering the time span of 1st April 2005 till 31st March 2019, to account for any difference existence in both. The study is conducted to judge the performance of gold futures as a tool of risk management. The result reveals the fact that hedging effectiveness from both the methodologies are found to be 35%. The reason behind low hedging efficiency might be due to the fact that gold itself is used as a hedge instrument and always in demand by the Indian investors for varied reasons as well as its accessibility in various forms (Gold ETFs and Gold Bonds issued by Government). The hedgers’ participation may be less as compared to speculators with respect gold future hedging. The results of phase-wise analysis, that is, before crisis (2005–2007), the hedging efficiency comes out to be 26%, during the crisis (2008–2012) 38.7% and after the crisis (2013–2018) 40% from both the static and dynamic hedge ratio models. The results showed that with the outbreak of Global Financial crisis in 2007–2009 and European debt crisis in 2010–2012 and thereafter, gold futures are increasing use as a risk management tool, but still at a minimal level.

Limitation of Aligners and How to Overcome Them

Aligners are a popular choice for many people seeking Orthodontic treatment due to their aesthetic appeal and convenience. They offer a more discreet alternative to traditional braces, as they are difficult to notice when worn. Along with that it provides an excellent substitute in the era of three-dimensional treatment planning. Clear aligners gradually exert gentle forces on the teeth, moving them incrementally until they reach the desired alignment. The aligner trays are designed to apply pressure to specific areas of your teeth, gradually shifting them into the correct position. The treatment process continues until all the teeth are properly aligned and bite is optimized. Earlier clear aligner treatment was considered to be utilized for the simpler cases, but with advancements it is proved that aligners can be one of the many possibilities for extraction cases, open bite, deep bite, interceptive and even for hybrid approaches. However, aligners may not be suitable for all Orthodontic treatment modalities, especially those requiring significant jaw alignment or complex tooth movements. This review focuses on the limitations and constraints of the type of movements provided by the clear aligners. Furthermore, this will assess the possibilities to overcome these obstacles for better performances in the near future.

Research on educational applications based on diagnostic learning analytics in the context of big data analytics

Abstract In the context of the significant data era, this paper explores the educational applications based on diagnostic learning analytics technology to improve personalized learning and teaching effects in the educational process. The study adopts a multidimensional feature fusion approach to construct a cognitive diagnostic model to predict learners’ knowledge status and future learning performance. Through actual data testing, the model can effectively predict the students’ knowledge mastery state and analyze the students’ learning process in depth. The experimental results show that the diagnostic model exhibits high efficiency and accuracy in predicting students’ knowledge mastery status, with an accuracy rate of 92.97%, significantly better than traditional teaching methods. In addition, the study explores the encoding method of learners’ multidimensional features and constructs a dynamic diagnostic model of test factors and student factors based on graph attention network. The study provides a new learning analysis and diagnostic method in the education field, which helps improve the effect of personalized learning.

Balancing Energy and Material Efficiency in Green Hydrogen Production via Water Electrolysis

Green hydrogen is increasingly regarded as a pivotal solution in achieving “net zero by 2050” in carbon neutrality across various sectors and industries. Ambitious decarbonisation roadmaps largely depend on the successful deployment of electrolysis technologies. Among these, Proton Exchange Membrane Electrolysis (PEMEL) stands out for its efficiency, compact design, and adaptability to intermittent renewable power sources. PEMEL is gradually being commercialised, and considerable uncertainty remains regarding its future environmental performance at a plant level. Therefore, future PEMEL cells should be life cycle engineered with a focus on improving materials efficiency by investigating enhanced electrochemical catalysts, membranes, and electrodes for an improved membrane electrode assembly (MEA). In this study, we simulate a 10MW PEMEL plant, identify key operational parameters and evaluate future MEA development scenarios to assess their impact on energy consumption, material utilisation, and system durability. Our findings shed light on the potential trade-offs between energy and material efficiency, providing valuable insights to mitigate environmental hotspots. By focusing on these trade-offs, this work contributes significantly to the ongoing efforts to improve the environmental and operational performance of PEMEL plants.

Novel multi-beam front end for LANSCE accelerator facility

The LANSCE accelerator facility has been in operation for 50 years performing important scientific support for national security. The unique feature of the LANSCE accelerator facility is multi-beam operation, delivering beams to five experimental areas. To reduce long-term operational risks and to realize future beam performance goals in support of the laboratory missions, we are developing a novel high-brightness Front End injector. The proposed injector includes two independent low-energy transports for H+ and H- beams merging beams at the entrance of a single RFQ. These beamlines also perform preliminary beam bunching before RFQ. The challenge of the present project is associated with the simultaneous acceleration of protons and H- ions with multiple beam flavors in a single RFQ, which has never been done before. The proposed injector must provide better than existing beam parameters while beam intensity is supposed to be increased by a factor of two and injection energy is reduced from 750 keV to 100 keV. The paper discusses the details of the design and presents injector parameters.

Novel majority carrier accumulation insulated gate bipolar transistor with Schottky junction

Insulated gate bipolar transistor (IGBT) is the core of modern power semiconductor device, and has been widely used due to its excellent electrical characteristics. A novel majority carrier accumulation mode IGBT with Schottky junction contact gate semiconductor layer (AC-SCG IGBT) is proposed and investigated by TCAD simulation in this article. When the AC-SCG IGBT is in the on-state, a forward bias is applied to the gate. Due to the very low forward voltage drop (<i>V</i><sub>F</sub>) of the Schottky barrier diode, the potential of the gate semiconductor layer is almost equal to the gate potential, which can accumulate a large number of majority carrier electrons in the drift region. In addition to the electrons existing, these accumulated electrons increase the conductivity of the drift region, thus significantly reducing <i>V</i><sub>F</sub>. Therefore, the doping concentration of the drift region is not limited by <i>V</i><sub>F</sub>. The lightly doped drift region can make AC-SCG IGBT have a higher breakdown voltage (BV). Moreover, it also reduces the barrier capacitance in the turn-off process, thus the overall Miller capacitance is small, which can quickly turn off and reduce the turn-off time (<i>T</i><sub>off</sub>) and turn-off loss (<i>E</i><sub>off</sub>). The simulation results indicate that at the BV of 600 V, the <i>V</i><sub>F</sub> of 0.84 V for the proposed AC-SCG IGBT is reduced by 46.2% compared with that for the conventional IGBT (<i>V</i><sub>F</sub> of 1.56 V). The <i>E</i><sub>off</sub> of the AC-SCG IGBT (0.77 mJ/cm<sup>2</sup>) is reduced by 52.5% compared with that for the conventional IGBT (1.62 mJ/cm<sup>2</sup>), and the <i>T</i><sub>off</sub> (155.8–222.7 ns) is reduced by 30%. The contradiction between <i>V</i><sub>F</sub> and <i>E</i><sub>off</sub> is eliminated. In addition, the proposed AC-SCG IGBT has a better anti-latch-up capability and is coupled with its higher BV, so it has a larger forward biased safe operating area (FBSOA). The proposed novel structure meets the development requirements for future IGBT device performance, and has great significance for guiding the development of the power semiconductor device field.

The comparison of macroeconomic development between the united states and japan in recent in recent years is analyzed from nasdaq and nikkei index

The changes in the Nasdaq and Nikkei over the past in recent years offer valuable insights for evaluating macroeconomic developments in the United States and Japan. Through an analysis of these two indicators, this paper can initially draw conclusions about the state of both countries’ economies. Over the past three years, the Nasdaq index has exhibited a relatively stable growth trend, maintaining strong overall growth despite fluctuations caused by global uncertainties. This may reflect advancements in areas such as technological innovation and the Internet sector, as well as investors’ optimism regarding future prospects. In contrast, the Nikkei index has displayed a more intricate and volatile pattern during this same period. While there have been some gains, it has experienced an overall decline marked by shocks. This could be attributed to various challenges faced by Japan including an aging population, low growth rate, and declining corporate competitiveness. The objective of this paper is to explore a similar model that explains stock markets in both the US and Japan. Many long-term investors base their stock decisions on the assumption that corporate cash flows should grow alongside economic performance while considering a constant or slow-moving discount rate. Therefore, it is expected that stock returns may exhibit correlation with future economic performance. Another concern worth addressing is how deflation might impact real stock returns.

Exploring factors within an introductory course that influence students’ perception of chemistry

A large number of students across the globe each year enroll in general chemistry courses as an academic requirement to obtain their degree. Although many take chemistry courses, it is not a subject sought out by many as a potential career. In some instances, chemistry hinders students from achieving their career goals. A plethora of chemical education research has focused on improving student attitude, self-efficacy, and motivation to enhance academic performance and retention in chemistry. However, only a few reports focus on the factors that affect student perception and self-efficacy towards chemistry. These factors are important as they can help us implement targeted interventions to improve perceptions and self-efficacy as we seek to increase diversity in STEM fields. In this research study, the most influential factors that affect a student's perception of chemistry are uncovered, and whether these factors are related to gender identity, letter grade, or pursuit of chemistry as a career. For our study population, the course instructor and course structure are the two most influential factors in a student's perception of chemistry. In addition, academically low-achieving students (i.e., students who earned Cs or lower in a course) are more likely to list the course structure as an influential factor, and high-achieving students (i.e., students who earned Bs or higher in a course) are more likely to select the course instructor as an influential factor. The majority (66%) of students who selected the course instructor as an influential factor believed that they would perform well in future chemistry courses, while 47% of those who selected the course structure had the same belief in their future chemistry performance. Overall, less than 11% of the study population (51 of 447 students) were interested in pursuing chemistry as a career after completing CHEM 1. However, the answer to increasing the number of chemistry majors could be held within course design and teaching pedagogy. This research study seeks to highlight the relationship between gender and letter grade with factors that influence perception of chemistry, and we hope the results can guide instructors as they consider course structure and teaching pedagogy.

Low-loss weak-coupling 6-mode hollow-core negative curvature fiber based on symmetric double-ring nested tube

Few-mode optical fibers have played an increasingly important role in breaking through the transmission capacity limitations of single-mode optical fiber and alleviating the bandwidth crisis in optic fiber communication systems in recent years. Nevertheless, traditional solid core few-mode optical fibers usually suffer optical fiber nonlinearity and mode coupling, leading to mode crosstalk between channels. Hollow core negative curvature fibers (HC-NCF) have attracted widespread attention due to their advantages, such as low latency, low nonlinearity, low dispersion, low transmission loss, and large operating bandwidth. In this work, a novel low-loss few-mode HC-NCF with symmetrically double ring nested tube structure is designed, which supports six core modes including LP<sub>01</sub>, LP<sub>11</sub>, LP<sub>21</sub>, LP<sub>02</sub>, LP<sub>31<i>a</i></sub>, and LP<sub>31<i>b</i></sub>. The designed optical fiber is based on silica dioxide substrate and adopts a unique symmetrical double ring nested cladding structure, which can effectively suppress the coupling between the core mode and the cladding mode. The finite element method (FDE) is used to numerically analyze the properties of the proposed few-mode HC-NCF and optimize the structural parameters of the few-mode HC-NCF. Moreover, the confinement loss and bending loss of all core modes are investigated. The simulation results show that the proposed few-mode HC-NCF can support the independent transmission of six weakly coupled core modes (with the effective refractive index difference greater than 1×10<sup>–4</sup> between the adjacent core modes, which greatly avoids the coupling between the adjacent modes in the fiber core). In the 400 nm bandwidth (1.23–1.63 μm, covering the O, E, S, C, and L bands), all six modes in the fiber core maintain low loss transmission. Moreover, in the range of 1.3–1.63 μm, the confinement loss (CL) of LP<sub>01</sub>, LP<sub>11</sub> and LP<sub>21</sub> mode are all less than 1×10<sup>–3</sup> dB/m, and the CL of LP<sub>02</sub> and LP<sub>31<i>b</i></sub> mode are both less than 3×10<sup>–3</sup> dB/m. The CL of each mode reaches the lowest value at 1.4 μm, and the LP<sub>01</sub> mode has the lowest CL of 4.3×10<sup>–7</sup> dB/m. In addition, for a bending radius of 7 cm, each mode maintains the low bending loss characteristic in a certain operating wavelength range. In the range of 1.23–1.61 μm, the BL of LP<sub>01</sub> is less than 4.5×10<sup>–4</sup> dB/m, and the BL of LP<sub>11</sub> is less than 1.3×10<sup>–3</sup> dB/m. The tolerance analysis shows that even with the deviation of structural parameters of ±1%, the few-mode HC-NCF can still maintain the characteristic of low-loss and weak coupling. The designed few-mode HC-NCF has ultra-low CL and bending-insensitive characteristics while supporting independent transmission of six modes, which will find huge potential applications in future high performance mode division multiplexing systems.

Generating Task Reallocation Suggestions to Handle Contingencies in Human-Supervised Multi-Robot Missions

In a mission with significant uncertainty due to intermittent communications, delayed information flow, and robotic failures, the role of human supervisors is extremely challenging. As and when any new information arrives, humans must infer both the existing and predicted future states, identify potential contingencies, and update task assignments to robots rapidly. We propose methodologies for automated generation of task reallocation suggestions to humans to assist in the decision-making process. Our generated robot retasking plan minimizes a modified makespan of the mission, which incorporates task criticality and penalty for incomplete tasks. The plan considers the effects of potential mission contingencies on the tasks, the robots, and the future performance of the robots operating based on the previous task plans. Our method includes the incorporation of two optional tasks, i.e., relay and robot rescue, for performance improvement. The rescue task has probabilistic outcomes affecting the team size. One or more rescues are incorporated in a way that can minimize the expected value of the modified makespan overall possibilities of rescue outcomes. We have conducted performance evaluation using simulation, demonstrating the value of the optional tasks and performance enhancement using our method of incorporating them. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The work reported in this paper will be useful in applications where a team of agents is deployed to carry on a large-scale mission with communication constraints where the number of functional agents can change probabilistically. Typically, such uncertainty is encountered in applications that are challenging or dangerous in nature. Agents can have non-zero probabilities to fail while doing certain risky tasks and to get recovered by other agents. The proposed centralized multi-agent task reallocation method can help in proactively addressing potential contingencies in surveillance, search and rescue, or disaster relief to support resilient operations while having a supervisor in the higher chain of command.

The Future Performance Implications of Non-GAAP Firms’ Investments

The Future Performance Implications of Non-GAAP Firms’ Investments

Does Political Uncertainty Obfuscate Narrative Disclosure?

ABSTRACT We examine the relation between political uncertainty and narrative disclosure complexity in conference calls. Using firm-level political uncertainty, we find that political uncertainty is positively associated with firms’ disclosures complexity as measured by the Fog index. Decomposing complexity into two latent components—information and obfuscation—we show that political uncertainty significantly increases the obfuscation but has no impact on the information. Further analysis reveals that complex disclosure is motivated by expected poor future performance amid political uncertainty. We also show that, during periods of heightened political uncertainty, obfuscated disclosure is associated with reduced earnings informativeness, increased dispersion in analyst forecasts, and higher volatility in forecast revisions. These findings are robust to including and excluding sentences containing complex political bigrams when calculating Fog. Further evidence shows that, during periods of political uncertainty, managers tend to use a more ambiguous tone and provide scripted and shorter (longer) responses to analysts’ questions (presentations).

Employee Perceptions: Disjuncture between Goals of Performance Management Systems and Effective Implementation in South Africa

This study sought to investigate employee perceptions of the implementation of the Employee Performance Management Development System in a South African government department. Quantitative and qualitative data were collected from employees in the department in the form of an on-line survey. The primary findings reveal a large gap between the goal of the system and its implementation. The results of the study indicate employees perceive the EPMDS to be an ineffective and inefficient system, largely because supervisors and managers are not implementing it objectively. As a result, employees believe the system is not fairly applied in managing their performance. The study makes a significant contribution by illuminating the misalignment between the intent of the system and its actual implementation. It also points to managerial bias and the focus on punitive action rather than rewarding performance according to goal achievement and developing future performance. A major implication of the results is that the need for a monitoring function as, as required by an EPMDS directive and framework. Employees perceive its implementation to be unfair, marked by bias and punitive measures.

Boundaries of management performance measures (MPMs) disclosed in primary financial statements prepared in accordance with new standard planned to supersede IAS 1

Abstract We outline the management performance measures (MPMs)' boundaries based on the upcoming introduction of MPM's definition to International Financial Reporting Standards (IFRS). The literature investigates business performance measures concentrating on managers' needs, while IFRS aims to provide financial information to external users who provide resources to the entity. This indicates a gap between how performance metrics have been investigated so far and how IFRS will adopt them. We used analysis of the exposure draft of the planned standard together with working materials developed in the consultation process. Further, a case study is presented. Results show that the scope of MPM to be introduced to IFRS is limited compared to the broad spectrum of performance measures presented in the literature. We contribute by showing the avenues for future performance measures research using signalling and agency theory and by indicating the limited scope of MPMs and thus bound prospects for using them for a full assessment of the entity‘s performance.

The usefulness of comprehensive income in predicting future performance: Evidence from the developing market

Based on the original study of Dhaliwal et al. (1999), this study examines empirically the usefulness of comprehensive income (CI) in predicting firms’ future performance comparing to net income (NI), using Jordanian firms listed in the Amman Stock Exchange (ASE) during the period 2010–2018. Two measures of company’ performance are employed, leading NI and cash flow from operation (CFO). We hypothesize that NI is more useful than CI in predicting future earnings and firm future CFO. Similarly, the empirical findings by Biddle and Choi (2006) also indicate that both measures NI and CI are significantly and positively associated with firm’s future performance measured by leading NI and CFO. However, the results show that NI is superior to CI in predicting future earnings and firm future CFO. These results hold for the alternative performance measures used in the analysis. Our findings also show a larger standard deviation for CI than NI indicating higher volatility of CI than NI. The superiority of NI is likely to be due the higher volatility of CI and the transitory nature of other comprehensive income (OCI) components included in CI but not included in NI. This study adds to the literature by examining the value relevance of NI and CI in an emerging market.

A Wavelet Analysis of Bitcoin Price Volatility Dynamic

The cryptocurrency market has experienced significant growth in international finance in recent years, attracting a large number of investors. This has led to a substantial increase in the overall trading volume[1], surpassing 1.2 trillion USD in July2023. Bitcoin in particular, has garnered significant interest from both advanced and emerging economies. Notably, Bitcoin is legal tender in El Salvador and the Central African Republic. The cryptocurrency market possesses distinct characteristics that set it apart from traditional markets such as exchanges, commodities, and equities. Its decentralization, facilitated by Blockchain technology, stands as a key differentiating factor. This technology enables anonymous trading of cryptocurrencies, with the identities of market participants, account holders, and electronic wallet managers remaining unknown. Consequently, there is an inherent ambiguity when it comes to characterizing the behavior of these investors or determining their preferred trading horizons. In this context, an important question arises: how do investors in the cryptocurrency market navigate price volatility? Furthermore, how do their trading strategies, which are inherently tied to their investment horizons, impact each other and consequently influence market prices? The heterogeneity hypothesis, which is a prevalent assumption in financial markets, is particularly relevant when exploring how investors in the cryptocurrency market navigate price volatility. The diverse trading strategies and approaches to handling price fluctuations among heterogeneous investors impact and influence the overall volatility and price dynamics of cryptocurrencies. The heterogeneity market hypothesis[2] refers to the existence of differences among investors or traders regarding their beliefs, information, risk preferences, investment strategies, and time horizons. In a heterogeneous market, investors, traders and financial institutions have varying views and expectations about the future performance of assets. These differences can manifest in various ways, such as market information access, market liquidity provision, trading strategies and market structure. While numerous empirical studies have explored the concept of market heterogeneity in relation to traditional assets such as those conducted by Müller et al. (1993;1997), Lux and Marchesi (2000), LeBaron (2000), Dacorogna et al. (2001) and Benhmad (2011), there is a paucity of research on this topic specifically focusing on cryptocurrencies. This paper aims to contribute to the existing literature that investigates the hypothesis of investor heterogeneity in traditional markets, including forex, stocks, and commodities. Specifically, we focus on the cryptocurrency market, which is predominantly dominated by Bitcoin. As of November 2021[3], Bitcoin holds the distinction of being the most actively traded cryptocurrency, with a market capitalization exceeding 1.2 trillion USD. Given its significance, Bitcoin garners substantial interest from investors across various categories. Therefore, this research seeks to uncover potential synergies among participants[4] in the cryptocurrency market and identify investor types and investment horizons prevalent in this market. By understanding these factors, we can gain insights into the dynamic volatility displayed by Bitcoin’s price. To tackle this issue, we investigate Bitcoin’s price volatility, analyzing causal relationships among short-term, medium and long-term traders by using wavelet transform to decompose volatility at different trading frequency scales[5] considered, then Granger causality test will be employed to determine if changes in one scale impact others. Furthermore, we extend this analysis by employing the nonlinear causality test proposed by Hmamouche. Y (2020). This nonlinear causality test goes beyond the limitations of the linear causality test and helps identifying potential nonlinear causal effects that may exist between the volatilities at different frequency scales, which could be overlooked by the linear causality test. The rest of this paper is organized as follows: Section 2 presents the theoretical framework relatively to the heterogeneity market hypothesis. Section 3 focuses on the empirical review. Section 4 and 5 turns to the data and methodology. Section 6 provides the empirical findings. Section 7 concludes.

ADJUDICATION OF MUSIC PERFORMANCES IN THREE SELECTED MUNICIPALITY/ DISTRICT IN GHANA

This paper presents an inquiry into the adjudication of music performances during cultural festivals within two municipalities and one district in the Central Region of Ghana. It examines the competence levels of adjudicators engaged in the process and elucidates the employed adjudication process, aiming to foster understanding and appreciation among all competition participants. Guided by Dworkin’s theory of interpretation, which delineates pre-interpretive, interpretive, and post-interpretive stages in adjudication, the research adopts a qualitative paradigm, utilizing interviews and document analysis as primary data collection instruments. Convenience and purposive sampling were employed to select both the geographical area and study participants respectively. The findings indicate that the selection of adjudicators is the prerogative of cultural coordinators, resulting in a less competitive process that may compromise competence in adjudication. Furthermore, although the cultural festival employs a scoring system across various disciplines to ensure precision and equity through expert adjudication, adjudicators struggle to provide comprehensive feedback that could aid participating groups in improving future performances. The paper suggests the establishment of strategies to introduce competitiveness in the engagement of adjudicators, coupled with plans to ensure their training as part of the preinterpretive stage before proceeding to the interpretive and post-interpretive stages. This approach aims to enhance the overall quality and effectiveness of the adjudication process.